Proteomic and immunoproteomic characterization of a DIVA subunit vaccine against Actinobacillus pleuropneumoniae

<p>Abstract</p> <p>Background</p> <p>Protection of pigs by vaccination against <it>Actinobacillus pleuropneumoniae</it>, the causative agent of porcine pleuropneumonia, is hampered by the presence of 15 different serotypes. A DIVA subunit vaccine comprised of detergent-released proteins from <it>A. pleuropneumoniae </it>serotypes 1, 2 and 5 has been developed and shown to protect pigs from clinical symptoms upon homologous and heterologous challenge. This vaccine has not been characterized in-depth so far. Thus we performed i) mass spectrometry in order to identify the exact protein content of the vaccine and ii) cross-serotype 2-D immunoblotting in order to discover cross-reactive antigens. By these approaches we expected to gain results enabling us to argue about the reasons for the efficacy of the analyzed vaccine.</p> <p>Results</p> <p>We identified 75 different proteins in the vaccine. Using the PSORTb algorithm these proteins were classified according to their cellular localization. Highly enriched proteins are outer membrane-associated lipoproteins like OmlA and TbpB, integral outer membrane proteins like FrpB, TbpA, OmpA1, OmpA2, HgbA and OmpP2, and secreted Apx toxins. The subunit vaccine also contained large amounts of the ApxIVA toxin so far thought to be expressed only during infection. Applying two-dimensional difference gel electrophoresis (2-D DIGE) we showed different isoforms and variations in expression levels of several proteins among the strains used for vaccine production. For detection of cross-reactive antigens we used detergent released proteins of serotype 7. Sera of pigs vaccinated with the detergent-released proteins of serotypes 1, 2, and 5 detected seven different proteins of serotype 7, and convalescent sera of pigs surviving experimental infection with serotype 7 reacted with 13 different proteins of the detergent-released proteins of <it>A. pleuropneumoniae </it>serotypes 1, 2, and 5.</p> <p>Conclusions</p> <p>A detergent extraction-based subunit vaccine of <it>A. pleuropneumoniae </it>was characterized by mass spectrometry. It contained a large variety of immunogenic and virulence associated proteins, among them the ApxIVA toxin. The identification of differences in expression as well as isoform variation between the serotypes implied the importance of combining proteins of different serotypes for vaccine generation. This finding was supported by immunoblotting showing the induction of cross-reactive antibodies against several surface associated proteins in immunized animals.</p

Automated Detection of Side Channels in Cryptographic Protocols: DROWN the ROBOTs!

Currently most practical attacks on cryptographic protocols like TLS are based on side channels, such as padding oracles. Some well-known recent examples are DROWN, ROBOT and Raccoon (USENIX Security 2016, 2018, 2021). Such attacks are usually found by careful and time-consuming manual analysis by specialists. In this paper, we consider the question of how such attacks can be systematically detected and prevented before (large-scale) deployment. We propose a new, fully automated approach, which uses supervised learning to identify arbitrary patterns in network protocol traffic. In contrast to classical scanners, which search for known side channels, the detection of general patterns might detect new side channels, even “unexpected” ones, such as those from the ROBOT attack. To analyze this approach, we develop a tool to detect Bleichenbacher-like padding oracles in TLS server implementations, based on an ensemble of machine learning algorithms. We verify that the approach indeed detects known vulnerabilities successfully and reliably. The tool also provides detailed information about detected patterns to developers, to assist in removing a potential padding oracle. Due to the automation, the approach scales much better than manual analysis and could even be integrated with a CI/CD pipeline of a development environment, for example

Controlled Crystal Growth of Indium Selenide, In2Se3, and the Crystal Structures of α-In2Se3

In2Se3 has been known for over 100 years and recently attracted interest as a promising candidate for a variety of applications, such as solar cells, photodiodes, and phase-change memories. Despite the broad concern for possible uses, its polymorphism and structure are poorly characterized. By combining X-ray diffraction, transmission electron microscopy, and quantum-chemical calculations, we present here the crystal structures of two layered room-temperature polytypes: 3R and 2H In2Se3. Both polymorphs are stacking variants of the same Se–In–Se–In–Se layers comprising two coordination environments for the In atoms, one tetrahedral and one octahedral. By using chemical-bonding analysis, we look at the different In positions in α-In2Se3 and compare them to those in the metastable β-phase