Bacteria of the phylum Planctomycetes have been previously reported to possess several features that are typical of eukaryotes, such as cytosolic compartmentalization and endocytosis-like macromolecule uptake. However, recent evidence points towards a Gram-negative cell plan for Planctomycetes, although in-depth experimental analysis has been hampered by insufficient genetic tools. Here we develop methods for expression of fluorescent proteins and for gene deletion in a model planctomycete, Planctopirus limnophila, to analyse its cell organization in detail. Super-resolution light microscopy of mutants, cryo-electron tomography, bioinformatic predictions and proteomic analyses support an altered Gram-negative cell plan for Planctomycetes, including a defined outer membrane, a periplasmic space that can be greatly enlarged and convoluted, and an energized cytoplasmic membrane. These conclusions are further supported by experiments performed with two other Planctomycetes, Gemmata obscuriglobus and Rhodopirellula baltica. We also provide experimental evidence that is inconsistent with endocytosis-like macromolecule uptake; instead, extracellular macromolecules can be taken up and accumulate in the periplasmic space through unclear mechanisms.
The periplasmic cytochrome cd1 nitrite reductase NirS occurring in denitrifying bacteria such as the human pathogen Pseudomonas aeruginosa contains the essential tetrapyrrole cofactors haem c and haem d1. Whereas the haem c is incorporated into NirS by the cytochrome c maturation system I, nothing is known about the insertion of the haem d1 into NirS. Here, we show by co-immunoprecipitation that NirS interacts with the potential haem d1 insertion protein NirN in vivo. This NirS–NirN interaction is dependent on the presence of the putative haem d1 biosynthesis enzyme NirF. Further, we show by affinity co-purification that NirS also directly interacts with NirF. Additionally, NirF is shown to be a membrane anchored lipoprotein in P. aeruginosa. Finally, the analysis by UV–visible absorption spectroscopy of the periplasmic protein fractions prepared from the P. aeruginosa WT (wild-type) and a P. aeruginosa ΔnirN mutant shows that the cofactor content of NirS is altered in the absence of NirN. Based on our results, we propose a potential model for the maturation of NirS in which the three proteins NirS, NirN and NirF form a transient, membrane-associated complex in order to achieve the last step of haem d1 biosynthesis and insertion of the cofactor into NirS.
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 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.
MetaQuant is written in Java and is available under an open source license. Precompiled packages for the installation on Windows or Linux operating systems are freely available for download. The source code as well as the installation packages are available at http://bioinformatics.org/metaquant
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