Structure-function relationships underpin disulfide loop cleavage-dependent activation of Legionella pneumophila lysophospholipase A PlaA

Legionella pneumophila, the causative agent of a life-threatening pneumonia, intracellularly replicates in a specialized compartment in lung macrophages, the Legionella-containing vacuole (LCV). Secreted proteins of the pathogen govern important steps in the intracellular life cycle including bacterial egress. Among these is the type II secreted PlaA which, together with PlaC and PlaD, belongs to the GDSL phospholipase family found in L. pneumophila. PlaA shows lysophospholipase A (LPLA) activity which increases after secretion and subsequent processing by the zinc metalloproteinase ProA within a disulfide loop. Activity of PlaA contributes to the destabilization of the LCV in the absence of the type IVB-secreted effector SdhA. We here present the 3D structure of PlaA which shows a typical α/β-hydrolase fold and reveals that the uncleaved disulfide loop forms a lid structure covering the catalytic triad S30/D278/H282. This leads to reduction of substrate access before activation; however, the catalytic site gets more accessible when the disulfide loop is processed. After structural modeling, a similar activation process is suggested for the GDSL hydrolase PlaC, but not for PlaD. Furthermore, the size of the PlaA substrate-binding site indicated preference toward phospholipids comprising ~16 carbon fatty acid residues which was verified by lipid hydrolysis, suggesting a molecular ruler mechanism. Indeed, mutational analysis changed the substrate profile with respect to fatty acid chain length. In conclusion, our analysis revealed the structural basis for the regulated activation and substrate preference of PlaA.

Towards the characterization of the hidden world of small proteins in Staphylococcus aureus, a proteogenomics approach

Small proteins play essential roles in bacterial physiology and virulence, however, automated algorithms for genome annotation are often not yet able to accurately predict the corresponding genes. The accuracy and reliability of genome annotations, particularly for small open reading frames (sORFs), can be significantly improved by integrating protein evidence from experimental approaches. Here we present a highly optimized and flexible bioinformatics workflow for bacterial proteogenomics covering all steps from (i) generation of protein databases, (ii) database searches and (iii) peptide-to-genome mapping to (iv) visualization of results. We used the workflow to identify high quality peptide spectrum matches (PSMs) for small proteins (≤ 100 aa, SP100) in Staphylococcus aureus Newman. Protein extracts from S. aureus were subjected to different experimental workflows for protein digestion and prefractionation and measured with highly sensitive mass spectrometers. In total, 175 proteins with up to 100 aa (SP100) were identified. Out of these 24 (ranging from 9 to 99 aa) were novel and not contained in the used genome annotation.144 SP100 are highly conserved and were found in at least 50% of the publicly available S. aureus genomes, while 127 are additionally conserved in other staphylococci. Almost half of the identified SP100 were basic, suggesting a role in binding to more acidic molecules such as nucleic acids or phospholipids.