Background
Community acquired pneumonia (CAP) is of high importance being the third most common cause of death worldwide. One third of all CAP-patients, which need admission to intensive care, derive from Legionnaires’ disease. However, the molecular interactions between host and pathogen are only partially resolved. Therefore, we used a human alveolar macrophages Legionella pneumophila infection model to profile the interplay of both partners by proteomics. Since such studies are often hampered by low sample amounts, we optimised a bead-based sample preparation protocol to enable comprehensive proteomics analysis of low L. pneumophila cell numbers and its corresponding host upon internalization.
Methodologies
L. pneumophila was cultivated in BCYE medium and 2x106 or 5x106 bacteria were filtered. Bacteria on filters were comparatively processed using three different cell disruption and digestion methods. A combination of SDS based cell disruption und tryptic digestion with an adapted single pot solid phase sample preparation (SP3) protocol was finally used in an infection assay. Samples of THP-1 cells and L. pneumophila Corby were generated by cell sorting using a FACSAriaTM 8 h, 12 h, and 16 h post infection. Finally, peptides of host and pathogen prepared with the optimized workflow were analyzed by nanoLC-MS/MS with a Q ExactiveTM Plus mass spectrometer.
Results
Coverage of the L. pneumophila proteome was increased up to 300% at the protein level and up to 620% at the peptide level with accompanied improvements in reproducibility, protein quantification, and data completeness. Overall, 1650 L. pneumophila proteins and 2967 THP-1 proteins were identified and quantified from the infection setting. Time-resolved, interdependent changes in the proteomes of pathogen and host will be discussed in the presentation.
Concluding statement
The adapted SP3-protocol in combination with harsh cell disruption enables strongly increased protein and peptide identification and therefore, allows new insights into host-pathogen interactions during infections.