Clinical metaproteomics workflow to study host-microbiome dynamics

Clinical metaproteomics has the potential to offer insights into the host-microbiome interactions underlying diseases. However, the field faces challenges in characterizing microbial proteins found in clinical samples, which are usually present at low abundance relative to the host proteins. As a solution, we have developed an integrated workflow coupling mass spectrometry-based analysis with customized bioinformatic identification, quantification, and prioritization of microbial proteins, enabling targeted assay development to investigate host-microbe dynamics in disease. The bioinformatics tools are implemented in the Galaxy ecosystem which offers integrated development and dissemination of complex bioinformatic workflows. The modular workflow integrates MetaNovo (to generate a reduced protein database), SearchGUI/PeptideShaker and MaxQuant (to generate peptide-spectral matches (PSMs) and quantification), PepQuery2 (to verify the quality of PSMs), Unipept (for taxonomic and functional annotation), and MSstatsTMT (for statistical analysis). We have utilized this workflow in ongoing projects to identify microbial peptide panels for cystic fibrosis (CF) disease progression studies, co-infection status during COVID-19 pandemic waves, and ovarian cancer biomarker discovery.

In the CF study, broncho-alveolar samples from pediatric CF and disease control patients were characterized for their microbial diversity. In addition to the above described modules, targeted analysis of microbial and host proteins from individual samples led to detection of a peptide-panel that includes known and novel peptide targets that can be used to track host-microbe protein dynamics during CF progression.

In another study, nasopharyngeal swabs from SARS-CoV-2 infected patients from a hospital in Mumbai, India, were analyzed to identify microbial peptides corresponding to potential co-infecting microorganisms during two pandemic waves. The study detected several peptides belonging to opportunistic microbial pathogens, such as Streptococcus pneumoniae, Klebsiella pneumoniae, Rhizopus microsporus, and Syncephalastrum racemosum. Microbial proteins with a role in stress response, gene expression, and DNA repair were upregulated in severe COVID-19 patients compared to those who tested negative for SARS-CoV-2.

Lastly, we analyzed Papanicolaou (Pap) test protein samples from benign, normal, and ovarian cancer patients for host and microbial proteins that are differentially expressed. The results of the quantitative analysis of these samples, and the potential use of combined host-microbe protein markers for cancer detection, will be discussed during the presentation.

The complete workflow, including training data and documentation, is available via the Galaxy Training Network, empowering non-expert researchers to utilize these powerful tools in their clinical studies. https://training.galaxyproject.org/training-material/learning-pathways/clinical-metaproteomics.html