Optimizing the Timing and Composition of Therapeutic Phage Cocktails: A Control-Theoretic Approach

Multi-strain phage induced clearance of bacterial infections

Bacteriophage (or 'phage' - viruses that infect and kill bacteria) are increasingly considered as a therapeutic alternative to treat antibiotic-resistant bacterial infections. However, bacteria can evolve resistance to phage, presenting a significant challenge to the near- and long-term success of phage therapeutics. Application of mixtures of multiple phages (i.e., 'cocktails') has been proposed to limit the emergence of phage-resistant bacterial mutants that could lead to therapeutic failure. Here, we combine theory and computational models of in vivo phage therapy to study the efficacy of a phage cocktail, composed of two complementary phages motivated by the example of Pseudomonas aeruginosa facing two phages that exploit different surface receptors, LUZ19v and PAK_P1. As confirmed in a Luria-Delbrück fluctuation test, this motivating example serves as a model for instances where bacteria are extremely unlikely to develop simultaneous resistance mutations against both phages. We then quantify therapeutic outcomes given single- or double-phage treatment models, as a function of phage traits and host immune strength. Building upon prior work showing monophage therapy efficacy in immunocompetent hosts, here we show that phage cocktails comprised of phage targeting independent bacterial receptors can improve treatment outcome in immunocompromised hosts and reduce the chance that pathogens simultaneously evolve resistance against phage combinations. The finding of phage cocktail efficacy is qualitatively robust to differences in virus-bacteria interactions and host immune dynamics. Altogether, the combined use of theory and computational analysis highlights the influence of viral life history traits and receptor complementarity when designing and deploying phage cocktails in immunocompetent and immunocompromised hosts.

Crossing the Chasm: How to Approach Translational Pharmacokinetic-Pharmacodynamic Modeling of Phage Dosing

Effectively treating multidrug-resistant bacterial infections remains challenging due to the limited drug development pipeline and a scarcity of novel agents effective against these highly resistant pathogens. Bacteriophages (phages) are a potential addition to the antimicrobial treatment arsenal. Though, phages are currently being tested in clinical trials for antibiotic-resistant infections, phages lack a fundamental understanding of optimal dosing in humans. Rationally designed preclinical studies using in vitro and in vivo infection models, allow us to assess clinically relevant phage +/- antibiotic exposure (pharmacokinetics), the resulting treatment impact on the infecting pathogen (pharmacodynamics) and host immune response (immunodynamics). A mechanistic modeling framework allows us to integrate this knowledge gained from preclinical studies to develop predictive models. We reviewed recently published mathematical models based on in vitro and/or in vivo data that evaluate the effects of varying bacterial or phage densities, phage characteristics (burst size, adsorption rate), phage pharmacokinetics, phage-antibiotic combinations and host immune responses. In our review, we analyzed study designs and the data used to inform the development of these mechanistic models. Insights gained from model-based simulations were reviewed as they help identify crucial phage parameters for determining effective phage dosing. These efforts contribute to bridging the gap between phage therapy research and its clinical translation.

Multi-strain phage induced clearance of bacterial infections

Bacteriophage (or 'phage' - viruses that infect and kill bacteria) are increasingly considered as a therapeutic alternative to treat antibiotic-resistant bacterial infections. However, bacteria can evolve resistance to phage, presenting a significant challenge to the near- and long-term success of phage therapeutics. Application of mixtures of multiple phage (i.e., 'cocktails') have been proposed to limit the emergence of phage-resistant bacterial mutants that could lead to therapeutic failure. Here, we combine theory and computational models of in vivo phage therapy to study the efficacy of a phage cocktail, composed of two complementary phages motivated by the example of Pseudomonas aeruginosa facing two phages that exploit different surface receptors, LUZ19v and PAK_P1. As confirmed in a Luria-Delbrück fluctuation test, this motivating example serves as a model for instances where bacteria are extremely unlikely to develop simultaneous resistance mutations against both phages. We then quantify therapeutic outcomes given single- or double-phage treatment models, as a function of phage traits and host immune strength. Building upon prior work showing monophage therapy efficacy in immunocompetent hosts, here we show that phage cocktails comprised of phage targeting independent bacterial receptors can improve treatment outcome in immunocompromised hosts and reduce the chance that pathogens simultaneously evolve resistance against phage combinations. The finding of phage cocktail efficacy is qualitatively robust to differences in virus-bacteria interactions and host immune dynamics. Altogether, the combined use of theory and computational analysis highlights the influence of viral life history traits and receptor complementarity when designing and deploying phage cocktails in immunocompetent and immunocompromised hosts.

Phages enhance both phytopathogen density control and rhizosphere microbiome suppressiveness

Bacteriophages, viruses that specifically target plant pathogenic bacteria, have emerged as a promising alternative to traditional agrochemicals. However, it remains unclear how phages should be applied to achieve efficient pathogen biocontrol and to what extent their efficacy is shaped by indirect interactions with the resident microbiota. Here, we tested if the phage biocontrol efficacy of Ralstonia solanacearum phytopathogenic bacterium can be improved by increasing the phage cocktail application frequency and if the phage efficacy is affected by pathogen-suppressing bacteria already present in the rhizosphere. We find that increasing phage application frequency improves R. solanacearum density control, leading to a clear reduction in bacterial wilt disease in both greenhouse and field experiments with tomato. The high phage application frequency also increased the diversity of resident rhizosphere microbiota and enriched several bacterial taxa that were associated with the reduction in pathogen densities. Interestingly, these taxa often belonged to Actinobacteria known for antibiotics production and soil suppressiveness. To test if they could have had secondary effects on R. solanacearum biocontrol, we isolated Actinobacteria from Nocardia and Streptomyces genera and tested their suppressiveness to the pathogen in vitro and in planta. We found that these taxa could clearly inhibit R. solanacearum growth and constrain bacterial wilt disease, especially when combined with the phage cocktail. Together, our findings unravel an undiscovered benefit of phage therapy, where phages trigger a second line of defense by the pathogen-suppressing bacteria that already exist in resident microbial communities.

IMPORTANCE

Ralstonia solanacearum is a highly destructive plant-pathogenic bacterium with the ability to cause bacterial wilt in several crucial crop plants. Given the limitations of conventional chemical control methods, the use of bacterial viruses (phages) has been explored as an alternative biological control strategy. In this study, we show that increasing the phage application frequency can improve the density control of R. solanacearum, leading to a significant reduction in bacterial wilt disease. Furthermore, we found that repeated phage application increased the diversity of rhizosphere microbiota and specifically enriched Actinobacterial taxa that showed synergistic pathogen suppression when combined with phages due to resource and interference competition. Together, our study unravels an undiscovered benefit of phages, where phages trigger a second line of defense by the pathogen-suppressing bacteria present in resident microbial communities. Phage therapies could, hence, potentially be tailored according to host microbiota composition to unlock the pre-existing benefits provided by resident microbiota.

The role of rhizosphere phages in soil health

While the One Health framework has emphasized the importance of soil microbiomes for plant and human health, one of the most diverse and abundant groups-bacterial viruses, i.e. phages-has been mostly neglected. This perspective reviews the significance of phages for plant health in rhizosphere and explores their ecological and evolutionary impacts on soil ecosystems. We first summarize our current understanding of the diversity and ecological roles of phages in soil microbiomes in terms of nutrient cycling, top-down density regulation, and pathogen suppression. We then consider how phages drive bacterial evolution in soils by promoting horizontal gene transfer, encoding auxiliary metabolic genes that increase host bacterial fitness, and selecting for phage-resistant mutants with altered ecology due to trade-offs with pathogen competitiveness and virulence. Finally, we consider challenges and avenues for phage research in soil ecosystems and how to elucidate the significance of phages for microbial ecology and evolution and soil ecosystem functioning in the future. We conclude that similar to bacteria, phages likely play important roles in connecting different One Health compartments, affecting microbiome diversity and functions in soils. From the applied perspective, phages could offer novel approaches to modulate and optimize microbial and microbe-plant interactions to enhance soil health.

Phage-host-immune system dynamics in bacteriophage therapy: basic principles and mathematical models

Phage therapy is progressively being recognized as a viable alternative to conventional antibiotic treatments, particularly in the context of multi-drug resistant bacterial challenges. However, the intricacies of the pharmacokinetics and pharmacodynamics (PKPD) pertaining to phages remain inadequately elucidated. A salient characteristic of phage PKPD is the inherent ability of phages to undergo replication. In this review, I proffer mathematical models that delineate the intricate dynamics encompassing the phage, the host organism, and the immune system. Fundamental tenets associated with proliferative and inundation thresholds are explored, and distinctions between active and passive therapies are accentuated. Furthermore, I present models that aim to illuminate the multifaceted interactions amongst diverse phage strains and bacterial subpopulations, each possessing distinct sensitivities to phages. The synergistic relationship between phages and the immune system is critically examined, demonstrating how the host's immunological function can influence the requisite phage dose for an optimal therapeutic outcome. A profound understanding of the presented modeling methodologies is paramount for researchers in the realms of clinical pharmacology and PKPD modeling interested in phage therapy. Such insights facilitate a more nuanced interpretation of dose-response relationships, enable the selection of potent phages, and aid in the optimization of phage cocktails.

Automating Predictive Phage Therapy Pharmacology

Viruses that infect as well as often kill bacteria are called bacteriophages, or phages. Because of their ability to act bactericidally, phages increasingly are being employed clinically as antibacterial agents, an infection-fighting strategy that has been in practice now for over one hundred years. As with antibacterial agents generally, the development as well as practice of this phage therapy can be aided via the application of various quantitative frameworks. Therefore, reviewed here are considerations of phage multiplicity of infection, bacterial likelihood of becoming adsorbed as a function of phage titers, bacterial susceptibility to phages also as a function of phage titers, and the use of Poisson distributions to predict phage impacts on bacteria. Considered in addition is the use of simulations that can take into account both phage and bacterial replication. These various approaches can be automated, i.e., by employing a number of online-available apps provided by the author, the use of which this review emphasizes. In short, the practice of phage therapy can be aided by various mathematical approaches whose implementation can be eased via online automation.

Structural Identifiability and Observability of Microbial Community Models

Biological communities are populations of various species interacting in a common location. Microbial communities, which are formed by microorganisms, are ubiquitous in nature and are increasingly used in biotechnological and biomedical applications. They are nonlinear systems whose dynamics can be accurately described by models of ordinary differential equations (ODEs). A number of ODE models have been proposed to describe microbial communities. However, the structural identifiability and observability of most of them-that is, the theoretical possibility of inferring their parameters and internal states by observing their output-have not been determined yet. It is important to establish whether a model possesses these properties, because, in their absence, the ability of a model to make reliable predictions may be compromised. Hence, in this paper, we analyse these properties for the main families of microbial community models. We consider several dimensions and measurements; overall, we analyse more than a hundred different configurations. We find that some of them are fully identifiable and observable, but a number of cases are structurally unidentifiable and/or unobservable under typical experimental conditions. Our results help in deciding which modelling frameworks may be used for a given purpose in this emerging area, and which ones should be avoided.

Oncolytic virus treatment of human breast cancer cells: Modelling therapy efficacy

Oncolytic viruses are a promising new treatment for cancer, whereby viruses are engineered to selectively destroy cancer cells. Mathematical modelling of the dynamics of the virus-tumour system can be modelled to provide insight into the system outcomes under different treatment protocols. In this study key metrics of treatment efficacy were identified and the mathematical model used to develop a decision framework to assess different treatment protocols. The optimal treatment outcome is the interplay between the virus application protocol and the uncertainty about the tumour characteristics. The uncertainty in the model parameters decreases as more data is available for their inference - however to obtain more data more time is required and the tumour then grows in size. Thus, there is an inherent tension whether it is better to wait to know the characteristics of the tumour system better or immediately initiating treatment. It is shown that, for small tumours, parameter inference with limited data does not constrain the choice of treatment protocol and rather only influences longer term decisions.

Phage-bacterial evolutionary interactions: experimental models and complications

Phage treatment of bacterial infections has offered some hope even as the crisis of antimicrobial resistance continues to be on the rise. However, bacterial resistance to phage is another looming challenge capable of undermining the effectiveness of phage therapy. Moreover, the consideration of including phage therapy in modern medicine calls for more careful research around every aspect of phage study. In an attempt to adequately prepare for the events of phage resistance, many studies have attempted to experimentally evolve phage resistance in different bacterial strains, as well as train phages to evolve counter-infectivity of resistant bacterial mutants, in view of answering such questions as coevolutionary dynamics between phage and bacteria, mechanisms of phage resistance, fitness costs of phage resistance on bacteria, etc. In this review, we summarised many such studies and by careful examination, highlighted critical issues to the outcome of phage therapy. We also discuss the insufficiency of many of these in vitro studies to represent actual disease conditions during phage application, alongside other complications that exist in phage-bacterial evolutionary interactions. Conclusively, we present the exploitation of phage-bacterial interactions for successful infection managements, as well as some future perspectives to direct phage research.

Pharmacokinetics/pharmacodynamics of phage therapy: a major hurdle to clinical translation

BACKGROUND

The increasing emergence of antimicrobial resistance worldwide has led to renewed interest in phage therapy. Unlike antibiotics, the lack of pharmacokinetics/pharmacodynamics (PK/PD) information represents a major challenge for phage therapy. As therapeutic phages are biological entities with the ability to self-replicate in the presence of susceptible bacteria, their PK/PD is far more complicated than that of antibiotics.

OBJECTIVES

This narrative review examines the current literature on phage pharmacology and highlights major pharmacological challenges for phage therapy.

SOURCES

Included articles were identified by searching PubMed and Google Scholar till June 2022. The search terms were 'bacteriophage', 'antimicrobial', 'pharmacokinetics' and 'pharmacodynamics'. Additional relevant references were obtained from articles retrieved from the primary search.

CONTENT

In this review, phage PK is first discussed, focusing on absorption, distribution, metabolism, and elimination. Key factors affecting phage antimicrobial activities are reviewed, including multiplicity of infection, passive and active phage therapy, and the involvement of the human immune system. Importantly, we emphasize the impact of phage self-replication on the PK/PD and the fundamental phage characteristics that are required for PK/PD modelling and clinical translation.

IMPLICATIONS

Recent progress in phage pharmacology has shown that we are in a far better position now to treat infections with phage therapy than a century ago. However, phage therapy is still in its infancy when compared to antibiotics due to the scarce pharmacological knowledge (e.g. PK/PD). Optimization of phage PK/PD is key for translation of phage therapy in patients.

The dynamic interplay of bacteriophage, bacteria and the mammalian host during phage therapy

For decades, biomedically centered studies of bacteria have focused on mechanistic drivers of disease in their mammalian hosts. Likewise, molecular studies of bacteriophage have centered on understanding mechanisms by which bacteriophage exploit the intracellular environment of their bacterial hosts. These binary interactions - bacteriophage infect bacteria and bacteria infect eukaryotic hosts - have remained largely separate lines of inquiry. However, recent evidence demonstrates how tripartite interactions between bacteriophage, bacteria and the eukaryotic host shape the dynamics and fate of each component. In this perspective, we provide an overview of different ways in which bacteriophage ecology modulates bacterial infections along a spectrum of positive to negative impacts on a mammalian host. We also examine how coevolutionary processes over longer timescales may change the valence of these interactions. We argue that anticipating both ecological and evolutionary dynamics is key to understand and control tripartite interactions and ultimately to the success or failure of phage therapy.

Recurrent ESBL Escherichia coli Urosepsis in a Pediatric Renal Transplant Patient Treated With Antibiotics and Bacteriophage Therapy

INTRODUCTION

Treating recurrent multidrug resistant (MDR) urosepsis in pediatric transplant recipients can be challenging. Particularly when antibiotics fail to prevent future occurrence and the nidus is seemingly undiscoverable. While there is an increasing amount of data on phage therapy, to our knowledge, there are no published cases involving pediatric renal transplant recipients. Therefore, we present a challenging clinical case in which phage therapy was used in a pediatric renal transplant recipient who developed recurrent MDR urosepsis with an unclear source.

CASE PRESENTATION

Our patient was a 17-year-old female who initially developed urosepsis caused by extended-spectrum β-lactamase (ESBL) Escherichia coli , while being treated with an immunosuppressant regimen because of kidney rejection secondary to poor immunosuppression therapy compliance. She was admitted to our hospital intermittently for 4 months with 4 episodes of urosepsis caused by ESBL E. coli . She received multiple courses of antibiotics (mainly ertapenem) and underwent a fecal material transplant to eradicate her ESBL E. coli colonized gastrointestinal tract. Because of recurrent development of urosepsis after antibiotic treatment, she later underwent treatment with a phage cocktail consisting of 2 isolate-specific phages. After a prolonged antibiotic course and subsequent 3-week intravenous phage treatment, she had no ESBL E. coli in her urinary cultures for 4 years post-treatment.

DISCUSSION

This case highlights the challenges of treating recurrent ESBL E. coli infections in a pediatric renal transplant patient and provides evidence that phage therapy may prove useful in such cases.

Reassessment of Historical Clinical Trials Supports the Effectiveness of Phage Therapy

Phage therapy has become a hot topic in medical research due to the increasing prevalence of antibiotic-resistant bacteria strains. In the treatment of bacterial infections, bacteriophages have several advantages over antibiotics, including strain specificity, lack of serious side effects, and low development costs. However, scientists dismissed the clinical success of early clinical trials in the 1940s, slowing the adoption of this promising antibacterial application in Western countries. The current study used statistical methods commonly used in modern meta-analysis to reevaluate early 20th-century studies and compare them with clinical trials conducted in the last 20 years. Using a random effect model, the development of disease after treatment with or without phages was measured in odds ratios (OR) with 95% confidence intervals (CI). Based on the findings of 17 clinical trials conducted between 1921 and 1940, phage therapy was effective (OR = 0.21, 95% CI = 0.10 to 0.44, P value < 0.0001). The current study includes a topic review on modern clinical trials; four could be analyzed, indicating a noneffective therapy (OR = 2.84, 95% CI = 1.53 to 5.27, P value = 0.0009). The results suggest phage therapy was surprisingly less effective than standard treatments in resolving bacterial infections. However, the results were affected by the small sample set size. This work also contextualizes the development of phage therapy in the early 20th century and highlights the expansion of phage applications in the last few years. In conclusion, the current review shows phage therapy is no longer an underestimated tool in the treatment of bacterial infections.

Cocktail, a Computer Program for Modelling Bacteriophage Infection Kinetics

Cocktail is an easy-to-use computer program for mathematical modelling of bacteriophage (phage) infection kinetics in a chemostat. The infection of bacteria by phages results in complicated dynamic processes as both have the ability to multiply and change during the course of an infection. There is a need for a simple way to visualise these processes, not least due to the increased interest in phage therapy. Cocktail is completely self-contained and runs on a Windows 64-bit operating system. By changing the publicly available source code, the program can be developed in the directions that users see fit. Cocktail's models consist of coupled differential equations that describe the infection of a bacterium in a vessel by one or two (interfering) phages. In the models, the bacterial population can be controlled by sixteen parameters, for example, through different growth rates, phage resistance, metabolically inactive cells or biofilm formation. The phages can be controlled by eight parameters each, such as different adsorption rates or latency periods. As the models in Cocktail describe the infection kinetics of phages in vitro, the program is primarily intended to generate hypotheses, but the results can however be indicative in the application of phage therapy.

Phage-Antibiotic Synergy Inhibited by Temperate and Chronic Virus Competition

As antibiotic resistance grows more frequent for common bacterial infections, alternative treatment strategies such as phage therapy have become more widely studied in the medical field. While many studies have explored the efficacy of antibiotics, phage therapy, or synergistic combinations of phages and antibiotics, the impact of virus competition on the efficacy of antibiotic treatment has not yet been considered. Here, we model the synergy between antibiotics and two viral types, temperate and chronic, in controlling bacterial infections. We demonstrate that while combinations of antibiotic and temperate viruses exhibit synergy, competition between temperate and chronic viruses inhibits bacterial control with antibiotics. In fact, our model reveals that antibiotic treatment may counterintuitively increase the bacterial load when a large fraction of the bacteria are antibiotic resistant, and both chronic and temperate phages are present.

Improving the Inhibitory Effect of Phages against Pseudomonas aeruginosa Isolated from a Burn Patient Using a Combination of Phages and Antibiotics

Antibiotic resistance causes around 700,000 deaths a year worldwide. Without immediate action, we are fast approaching a post-antibiotic era in which common infections can result in death. Pseudomonas aeruginosa is the leading cause of nosocomial infection and is also one of the three bacterial pathogens in the WHO list of priority bacteria for developing new antibiotics against. A viable alternative to antibiotics is to use phages, which are bacterial viruses. Yet, the isolation of phages that efficiently kill their target bacteria has proven difficult. Using a combination of phages and antibiotics might increase treatment efficacy and prevent the development of resistance against phages and/or antibiotics, as evidenced by previous studies. Here, in vitro populations of a Pseudomonas aeruginosa strain isolated from a burn patient were treated with a single phage, a mixture of two phages (used simultaneously and sequentially), and the combination of phages and antibiotics (at sub-minimum inhibitory concentration (MIC) and MIC levels). In addition, we tested the stability of these phages at different temperatures, pH values, and in two burn ointments. Our results show that the two-phages-one-antibiotic combination had the highest killing efficiency against the P. aeruginosa strain. The phages tested showed low stability at high temperatures, acidic pH values, and in the two ointments. This work provides additional support for the potential of using combinations of phage-antibiotic cocktails at sub-MIC levels for the treatment of multidrug-resistant P. aeruginosa infections.