A new study outlines how an innovative tool can be used to help uncover the reasons why phages succeed or fail when used to target bacterial infections.
This study, led by Ruizhe (Erez) Li of the University of Cambridge, was presented in a talk at the Viruses of Microbes (VOM) event earlier this year and was awarded the Sustainable Microbiology journal award for best scientific presentation at the conference.
Ruizhe described how the University of Cambridge team had developed a high-throughput single-cell phage infection tracking assay that allows them to quantify the kinetics of each step of phage infection in individual bacterial cells and correlate these parameters with the host’s physiological state.
This breakthrough provides a systems-level understanding of phage efficacy, revealing when and why phages succeed or fail in clearing their targets.
“Moreover, by understanding how infection parameters depend on bacterial physiology, we can design combination therapies that modulate bacterial physiology, making bacteria more susceptible to phage-mediated eradication, paving the way for more targeted and reliable antimicrobial strategies,” he said.
Combining expertise
This work was a collaboration between the Bakshi Lab in the Engineering Department and Diana Fusco’s lab in the Physics Department, combining expertise in single-cell imaging, microfluidics, phage engineering and quantitative modeling to advance the understanding of phage-bacteria interactions.
“We are addressing the challenge of harnessing phages as effective therapeutics and biocontrol agents by understanding how host physiology influences phage infection kinetics,” Ruizhe said.
“Like antibiotics, phages depend on the physiological state of their bacterial hosts, and an incomplete understanding of these dependencies can lead to tolerance and phenotypic resistance, making treatments unpredictable and less effective. Our goal is to determine how host physiology and its variability impact phage efficacy, enabling us to quantify escape and resistance rates at the single-cell level. By integrating these measurements into predictive models, we aim to improve the reliability of phage-based interventions at the population level.”
Lytic phage infections
To study lytic phage infections at the single-cell resolution and with sufficient throughput, the researchers developed a microfluidic-based infection assay that allows a large number of independent host cell lineages to be maintained under controlled homogeneous growth conditions, while they are infected by phages.
They had to design and optimise the microfluidic channels in this device to ensure that phages can diffuse efficiently to isolated linear colonies maintained in each trench (led by Charlie Wedd).
To track the infection steps, they used time-resolved fluorescence and brightfield imaging to monitor steps of infection from T7 phages that are engineered to contain a genomically integrated fluorescent marker (by Temur Yunusov in the Fusco lab).
This data was processed using machine-learning-based analysis tools (originally developed by another PhD student in the Bakshi lab, Georgeos Hardo (currently an Assistant Professor · United Arab Emirates University) and adapted to this task by Charlie Wedd and Ruizhe) to precisely track and quantify each stage of infection within individual cells, from adsorption to lysis.
Pipeline of information
This pipeline provided unprecedented information about the dynamics of each step in the infection process and its relation to the host cell parameters, such as their size, ribosome content, growth rate, etc.
READ MORE: The Microbiologist special issue on Bacteriophages
The next step was to harness the physiological heterogeneity of the infected cells and the heterogeneity of the infection kinetics, by building a mathematical model to relate the associated variabilities. This model of viral gene expression was built based on basic assumptions of how phage gene transcription was dependent on the viral RNAP, while the translation kinetics is dependent on the abundance of host ribosomes and the corresponding viral mRNA. This model was fit to the experimental data and the fit predicted that as the viral DNA replication progresses exponentially and the mRNAs are rapidly produced off the DNA, host ribosome occupation rapidly saturates.
Limiting factor
This result suggests that the host’s translation capacity becomes a limiting factor in phage gene expression, and possibly determines how many new phage particles can be made in a cell - an observation that was later verified using phage infections on a ribosome-labelled bacterial strain.
There was one unexpected finding, as Ruizhe explained: “Previous bulk studies which compare averages of population-level data from experiments conducted under different growth conditions or with different phage or host mutants have concluded that phage production scales linearly with the infection-to-lysis time.
“However, when we looked into the heterogeneity of infection kinetics within a population (from a pure host-phage genotype and under control constant growth condition), we found that instead the host physiological parameter (here ribosome content) was a stronger predictor of the phage gene expression and the time of infection to lysis had a weaker predictive power.
“This finding highlights the clarity of mechanistic interpretation from data collected at single-cell resolution, which does not blur and average the dynamics of unsynchronised infections across physiologically heterogeneous infected cells, as typically done in bulk measurements.”
Predicting phage effectiveness
By uncovering how bacterial physiology influences phage infection dynamics, we can predict conditions under which phages are most effective and identify scenarios where resistance or escape is likely, Ruizhe said.
“This knowledge is crucial for designing robust phage-based treatments that minimize failure rates. Furthermore, by leveraging small-molecule or antibiotic interventions to manipulate bacterial physiology, we can enhance phage efficacy, making treatments more predictable and adaptable to clinical and industrial applications.
“Additionally, our platform provides a powerful tool for screening both engineered and natural phages, enabling precise characterization of their infection dynamics and a deeper mechanistic understanding of their efficacy, ultimately guiding the development of optimized phage therapies.”
Additionally, the team is currently working towards developing a rapid phage susceptibility testing platform leveraging their microfluidic-microscopic phage infection tracking assay, for quickly screening and identifying potent phages to eradicate a target pathogenic bacterium.
Next steps
To build on these findings, future work will focus on expanding our single-cell infection tracking platform to a broader range of bacterial hosts and phages, including clinically relevant and engineered phages, he said.
“We also need to refine predictive models by integrating large-scale single-cell data with population-level infection dynamics.
“Finally, validating these insights in physiologically relevant infection models will be crucial for translating our findings into real-world therapeutic and biocontrol applications.”
The research has not yet been published but is based on the following two papers:
Topics
- Applied Microbiology International
- biocontrol agents
- Charlie Wedd
- Clinical & Diagnostics
- Community
- Diana Fusco
- Georgeos Hardo
- Innovation News
- Microbiological Methods
- One Health
- Phage Therapy
- Ruizhe (Erez) Li
- Temur Yunusov
- UK & Rest of Europe
- United Arab Emirates University
- University of Cambridge
- Viruses
- Viruses of Microbes
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