Next-generation proteomics for quantitative Jumbophage-bacteria interaction mapping.
Andrea FossatiDeepto MozumdarClaire KokontisMelissa Mèndez-MoranEliza S NieweglowskaAdrian PelinYuping LiBaron GuoNevan J KroganDavid A AgardJoseph Bondy-DenomyDanielle L SwaneyPublished in: Nature communications (2023)
Host-pathogen interactions are pivotal in regulating establishment, progression, and outcome of an infection. While affinity-purification mass spectrometry has become instrumental in characterizing such interactions, it suffers from limitations in scalability and biological authenticity. Here we present the use of co-fractionation mass spectrometry for high throughput analysis of host-pathogen interactions from native viral infections of two jumbophages (ϕKZ and ϕPA3) in Pseudomonas aeruginosa. This approach enabled the detection of > 6000 unique host-pathogen interactions for each phage, encompassing > 50% of their respective proteomes. This deep coverage provided evidence for interactions between KZ-like phage proteins and the host ribosome, and revealed protein complexes for previously undescribed phage ORFs, including a ϕPA3 complex showing strong structural and sequence similarity to ϕKZ non-virion RNA polymerase. Interactome-wide comparison across phages showed similar perturbed protein interactions suggesting fundamentally conserved mechanisms of phage predation within the KZ-like phage family. To enable accessibility to this data, we developed PhageMAP, an online resource for network query, visualization, and interaction prediction ( https://phagemap.ucsf.edu/ ). We anticipate this study will lay the foundation for the application of co-fractionation mass spectrometry for the scalable profiling of host-pathogen interactomes and protein complex dynamics upon infection.
Keyphrases
- pseudomonas aeruginosa
- mass spectrometry
- high resolution
- liquid chromatography
- cystic fibrosis
- candida albicans
- high throughput
- capillary electrophoresis
- biofilm formation
- amino acid
- gas chromatography
- acinetobacter baumannii
- high performance liquid chromatography
- healthcare
- escherichia coli
- machine learning
- electronic health record
- quantum dots