Enhancing the immunogenicity and modulating the fine epitope recognition of antisera to a helical group A streptococcal peptide vaccine candidate from the M protein using lipid-core peptide technology

A conserved helical peptide vaccine candidate from the M protein of group A streptococci, p145, has been described. Minimal epitopes within p145 have been defined and an epitope recognized by protective antibodies, but not by autoreactive T cells, has been identified. When administered to mice, p145 has low immunogenicity. Many boosts of peptide are required to achieve a high antibody titre (> 12 800). To attempt to overcome this low immunogenicity, lipid-core peptide technology was employed. Lipid-core peptides (LCP) consist of an oligomeric polylysine core, with multiple copies of the peptide of choice, conjugated to a series of lipoamino acids, which acts as an anchor for the antigen. Seven different LCP constructs based on the p145 peptide sequence were synthesized (LCP1-->LCP7) and the immunogenicity of the compounds examined. The most immunogenic constructs contained the longest alkyl side-chains. The number of lipoamino acids in the constructs affected the immunogenicity and spacing between the alkyl side-chains increased immunogenicity. An increase in immunogenicity (enzyme-linked immunosorbent assay (ELISA) titres) of up to 100-fold was demonstrated using this technology and some constructs without adjuvant were more immunogenic than p145 administered with complete Freund's adjuvant (CFA). The fine specificity of the induced antibody response differed for the different constructs but one construct, LCP4, induced antibodies of identical fine specificity to those found in endemic human serum. Opsonic activity of LCP4 antisera was more than double that of p145 antisera. These data show the potential for LCP technology to both enhance immunogenicity of complex peptides and to focus the immune response towards or away from critical epitopes.

The use of stochastic dynamic programming in optimal landscape reconstruction for metapopulations

A decision theory framework can be a powerful technique to derive optimal management decisions for endangered species. We built a spatially realistic stochastic metapopulation model for the Mount Lofty Ranges Southern Emu-wren (Stipiturus malachurus intermedius), a critically endangered Australian bird. Using diserete-time Markov,chains to describe the dynamics of a metapopulation and stochastic dynamic programming (SDP) to find optimal solutions, we evaluated the following different management decisions: enlarging existing patches, linking patches via corridors, and creating a new patch. This is the first application of SDP to optimal landscape reconstruction and one of the few times that landscape reconstruction dynamics have been integrated with population dynamics. SDP is a powerful tool that has advantages over standard Monte Carlo simulation methods because it can give the exact optimal strategy for every landscape configuration (combination of patch areas and presence of corridors) and pattern of metapopulation occupancy, as well as a trajectory of strategies. It is useful when a sequence of management actions can be performed over a given time horizon, as is the case for many endangered species recovery programs, where only fixed amounts of resources are available in each time step. However, it is generally limited by computational constraints to rather small networks of patches. The model shows that optimal metapopulation, management decisions depend greatly on the current state of the metapopulation,. and there is no strategy that is universally the best. The extinction probability over 30 yr for the optimal state-dependent management actions is 50-80% better than no management, whereas the best fixed state-independent sets of strategies are only 30% better than no management. This highlights the advantages of using a decision theory tool to investigate conservation strategies for metapopulations. It is clear from these results that the sequence of management actions is critical, and this can only be effectively derived from stochastic dynamic programming. The model illustrates the underlying difficulty in determining simple rules of thumb for the sequence of management actions for a metapopulation. This use of a decision theory framework extends the capacity of population viability analysis (PVA) to manage threatened species.

The t-SNARE syntaxin 4 is regulated during macrophage activation to function in membrane traffic and cytokine secretion

Activation of macrophages with lipopolysaccharide (LPS) induces the rapid synthesis and secretion of proinflammatory cytokines, such as tumor necrosis factor (TNFalpha), for priming the immune response [1, 2]. TNFalpha plays a key role in inflammatory disease [3]; yet, little is known of the intracellular trafficking events leading to its secretion. In order to identify molecules involved in this secretory pathway, we asked whether any of the known trafficking proteins are regulated by LPS. We found that the levels of SNARE proteins were rapidly and significantly up- or downregulated during macrophage activation. A subset of t-SNAREs (Syntaxin 4/SNAP23/Munc18c) known to control regulated exocytosis in other cell types [4, 5] was substantially increased by LPS in a temporal pattern coinciding with peak TNFalpha secretion. Syntaxin 4 formed a complex with Munc18c at the cell surface of macrophages. Functional studies involving the introduction of Syntaxin 4 cDNA or peptides into macrophages implicate this t-SNARE in a rate-limiting step of TNFalpha secretion and in membrane ruffling during macrophage activation. We conclude that in macrophages, SNAREs are regulated in order to accommodate the rapid onset of cytokine secretion and for membrane traffic associated with the phenotypic changes of immune activation. This represents a novel regulatory role for SNAREs in regulated secretion and in macrophage-mediated host defense.