Project Profiling microprotein interactions in bacterial pathogen infections; Jyoti Choudhary

Standard protein catalogs list only a fraction of what cells actually make. Scattered across genomes are many small open reading frames (smORFs), short stretches of sequence that are translated into microproteins, tiny proteins that reference catalogs have long overlooked. During a bacterial infection both the host and the pathogen switch on new programs of translation, and some of these overlooked microproteins are likely to play a role at the host-pathogen interface.

Detecting them in a system where host and bacterial proteins are mixed together is technically difficult and largely unexplored.

This project will map microproteins in host-pathogen interactions using Citrobacter rodentium, a model for enteric (gut) infection, combining a dual prokaryotic-eukaryotic proteomics workflow with ribosome profiling (Ribo-seq) to capture host and pathogen translation across the stages of infection. It sits in ORFeus Work Package 1 on uncovering the dark genome and proteome, where its dual-species workflow produces unique training data for the network's computational models.

The work connects closely to partner projects on AI-driven translation modeling, complementary microprotein proteomics, thermal proteome profiling, computational protein design, and antigen presentation.

• Map the microprotein landscape across three stages of infection, from early to peak to resolution, in mouse epithelial cell lines and in a C57BL
  /6 mouse model, building a dual prokaryotic-eukaryotic Ribo-seq and proteomics workflow that reads host and pathogen translation together.
• Probe the functions of infection-induced microproteins using proximity labeling (BioID) to map their interaction partners, separating genuinely infection-specific responses from general cellular stress across the stages of infection.
• Turn the approach into a dual prokaryotic-eukaryotic microprotein discovery workflow that other groups can adapt, validating BioID interaction maps with thermal proteome profiling together with other doctoral candidates (DCs) in the network, here DC10, and refining AI-driven peptide-spectrum matching during the industry secondment.
• Collaborate across the ORFeus network, providing dual-species training data for the computational models of DC1 and infection-associated microprotein targets for the antigen presentation work of DC14 and the protein-design work of DC6, contribute datasets to the shared ORFeome platform, and produce the project's scientific report.

Methods and platforms
: dual prokaryotic-eukaryotic mass-spectrometry proteomics and ribosome profiling (Ribo-seq), proximity labeling (BioID) for interaction mapping, targeted mass spectrometry (parallel reaction monitoring, PRM) for computationally predicted candidates, thermal proteome profiling (TPP), AI-driven peptide-spectrum matching, and Citrobacter rodentium infection models in mouse epithelial cell lines and in vivo, contributing data to the ORFeome platform.

Secondment
: you will spend around three months at Tesorai (San Francisco, USA), refining AI-driven peptide-spectrum matching for microprotein identification in the dual-species data. You will also be guided by an independent academic advisor, with the possibility of a short, primarily virtual research exchange to strengthen the project.

MSCA eligibility

You must meet all of the following on your recruitment date:

• You do not already hold a doctoral degree. If you have defended a doctoral thesis but the degree has not yet been formally awarded, you are not eligible.
• Mobility rule: you must not have lived or carried out your main activity (work, studies, and so on) in the United Kingdom for more than 12 months in the 36 months immediately before your recruitment date.…