The enigmatic return of cockroaches find more to ammonotely seems to be related to the role of bacterial endosymbiosis in their nitrogen economy. López-Sánchez et al. [1] showed the presence of urease activity in endosymbiont-enriched extracts of the cockroaches B.

germanica and P. americana. Stoichiometric analysis of the core of the Poziotinib mouse reconstructed metabolic networks would suggest that these endosymbiotic bacteria participate in the nitrogen metabolism of the host. Physiological studies ([1, 8] and references therein) suggest that uric acid may represent a form of nitrogen storage in cockroaches and that B. cuenoti may produce ammonia from uric-derived metabolites provided by the host. In fact, the cockroach fat body contains specialized cells storing uric acid (urocytes) that are in close proximity to the cells containing endosymbionts (bacteriocytes) [13]. A common feature of genomes from bacterial endosymbionts is their strict conservation of gene order and remarkable differential gene losses in the different lineages [14–16]. In the case of the Bge and Pam strains, comparative genomics reveals both a high degree of conservation in their chromosomal architecture and in the gene repertoires (accounting for a total of 627 and 619 genes in Bge and Pam, respectively) despite

the low sequence similarity observed (~85% nucleotide sequence identity) [6]. Thus, the metabolic networks of these endosymbionts should be similar, differing only slightly. These

differences might be analyzed from a qualitative point of view by comparison between R428 clinical trial the inferred metabolic maps, but this approach does not allow quantitative evaluation of how these inequalities might affect the functional capabilities of each microorganism. Constraint-based models Osimertinib in vitro of metabolic networks represent an efficient framework for a quantitative understanding of microbial physiology [17]. In fact, computational simulations with constraint-based models are approaches that help to predict cellular phenotypes given particular environmental conditions, with a high correspondence between experimental results and predictions [18–20]. It is worth mentioning that they are especially suitable for reconstructed networks from uncultivable microorganism, as it is the case of primary endosymbionts. Thus, Flux Balance Analysis (FBA) is one of these useful techniques for the study of obligate intracellular bacteria, since it reconstructs fluxes through a network requiring neither kinetic parameters nor other detailed information on enzymes [17]. This modeling method is based on the stoichiometric coefficients of each reaction and the assumption of the system at steady-state [21]. FBA calculates metabolites fluxes through the metabolic reactions that optimize an objective function –usually biomass production–, i.e., how much each reaction contributes to the phenotype desired. In this study, we have reconstructed the metabolic networks of Bge and Pam strains of B.