Kinetic analysis of PPi-dependent phosphofructokinase from Porphyromonas gingivalis

To Eat and to Be Eaten: Mutual Metabolic Adaptations of Immune Cells and Intracellular Bacterial Pathogens upon Infection

Intracellular bacterial pathogens (IBPs) invade and replicate in different cell types including immune cells, in particular of the innate immune system (IIS) during infection in the acute phase. However, immune cells primarily function as essential players in the highly effective and integrated host defense systems comprising the IIS and the adaptive immune system (AIS), which cooperatively protect the host against invading microbes including IBPs. As countermeasures, the bacterial pathogens (and in particular the IBPs) have developed strategies to evade or reprogram the IIS at various steps. The intracellular replication capacity and the anti-immune defense responses of the IBP's as well as the specific antimicrobial responses of the immune cells of the innate and the AIS depend on specific metabolic programs of the IBPs and their host cells. The metabolic programs of the immune cells supporting or counteracting replication of the IBPs appear to be mutually exclusive. Indeed, recent studies show that upon interaction of naïve, metabolically quiescent immune cells with IBPs, different metabolic activation processes occur which may result in the provision of a survival and replication niche for the pathogen or its eradication. It is therefore likely that within a possible host cell population subsets exist that are metabolically programmed for pro- or anti-microbial conditions. These metabolic programs may be triggered by the interactions between different bacterial agonistic components and host cell receptors. In this review, we summarize the current status in the field and discuss metabolic adaptation processes within immune cells of the IIS and the IBPs that support or restrict the intracellular replication of the pathogens.

The life stage-specific pathometabolism of Legionella pneumophila

The genus Legionella belongs to Gram-negative bacteria found ubiquitously in aquatic habitats, where it grows in natural biofilms and replicates intracellularly in various protozoa (amoebae, ciliates). L. pneumophila is known as the causative agent of Legionnaires' disease, since it is also able to replicate in human alveolar macrophages, finally leading to inflammation of the lung and pneumonia. To withstand the degradation by its host cells, a Legionella-containing vacuole (LCV) is established for intracellular replication, and numerous effector proteins are secreted into the host cytosol using a type four B secretion system (T4BSS). During intracellular replication, Legionella has a biphasic developmental cycle that alternates between a replicative and a transmissive form. New knowledge about the host-adapted and life stage-dependent metabolism of intracellular L. pneumophila revealed a bipartite metabolic network with life stage-specific usages of amino acids (e.g. serine), carbohydrates (e.g. glucose) and glycerol as major substrates. These metabolic features are associated with the differentiation of the intracellular bacteria, and thus have an important impact on the virulence of L. pneumophila.

Metabolic network model of a human oral pathogen

The microbial community present in the human mouth is engaged in a complex network of diverse metabolic activities. In addition to serving as energy and building-block sources, metabolites are key players in interspecies and host-pathogen interactions. Metabolites are also implicated in triggering the local inflammatory response, which can affect systemic conditions such as atherosclerosis, obesity, and diabetes. While the genome of several oral pathogens has been sequenced, quantitative understanding of the metabolic functions of any oral pathogen at the system level has not been explored yet. Here we pursue the computational construction and analysis of the genome-scale metabolic network of Porphyromonas gingivalis, a gram-negative anaerobe that is endemic in the human population and largely responsible for adult periodontitis. Integrating information from the genome, online databases, and literature screening, we built a stoichiometric model that encompasses 679 metabolic reactions. By using flux balance approaches and automated network visualization, we analyze the growth capacity under amino-acid-rich medium and provide evidence that amino acid preference and cytotoxic by-product secretion rates are suitably reproduced by the model. To provide further insight into the basic metabolic functions of P. gingivalis and suggest potential drug targets, we study systematically how the network responds to any reaction knockout. We focus specifically on the lipopolysaccharide biosynthesis pathway and identify eight putative targets, one of which has been recently verified experimentally. The current model, which is amenable to further experimental testing and refinements, could prove useful in evaluating the oral microbiome dynamics and in the development of novel biomedical applications.