Inhibition of the NLRP3 inflammasome improves lifespan in animal murine model of Hutchinson-Gilford Progeria.

Inflammation is a hallmark of aging and accelerated aging syndromes such as Hutchinson-Gilford progeria syndrome (HGPS). In this study, we present evidence of increased expression of the components of the NLRP3 inflammasome pathway in HGPS skin fibroblasts, an outcome that was associated with morphological changes of the nuclei of the cells. Lymphoblasts from HGPS patients also showed increased basal levels of NLRP3 and caspase 1. Consistent with these results, the expression of caspase 1 and Nlrp3, but not of the other inflammasome receptors was higher in the heart and liver of Zmpste24-/- mice, which phenocopy the human disease. These data were further corroborated in LmnaG609G/G609G mice, another HGPS animal model. We also showed that pharmacological inhibition of the NLRP3 inflammasome by its selective inhibitor, MCC950, improved cellular phenotype, significantly extended the lifespan of progeroid animals, and reduced inflammasome-dependent inflammation. These findings suggest that inhibition of the NLRP3 inflammasome is a potential therapeutic approach for the treatment of HGPS.

Coexistence of nestedness and modularity in host-pathogen infection networks.

The long-term coevolution of hosts and pathogens in their environment forms a complex web of multi-scale interactions. Understanding how environmental heterogeneity affects the structure of host-pathogen networks is a prerequisite for predicting disease dynamics and emergence. Although nestedness is common in ecological networks, and theory suggests that nested ecosystems are less prone to dynamic instability, why nestedness varies in time and space is not fully understood. Many studies have been limited by a focus on single habitats and the absence of a link between spatial variation and structural heterogeneity such as nestedness and modularity. Here we propose a neutral model for the evolution of host-pathogen networks in multiple habitats. In contrast to previous studies, our study proposes that local modularity can coexist with global nestedness, and shows that real ecosystems are found in a continuum between nested-modular and nested networks driven by intraspecific competition. Nestedness depends on neutral mechanisms of community assembly, whereas modularity is contingent on local adaptation and competition. The structural pattern may change spatially and temporally but remains stable over evolutionary timescales. We validate our theoretical predictions with a longitudinal study of plant-virus interactions in a heterogeneous agricultural landscape.

Population dynamics of synthetic terraformation motifs.

Ecosystems are complex systems, currently experiencing several threats associated with global warming, intensive exploitation and human-driven habitat degradation. Because of a general presence of multiple stable states, including states involving population extinction, and due to the intrinsic nonlinearities associated with feedback loops, collapse in ecosystems could occur in a catastrophic manner. It has been recently suggested that a potential path to prevent or modify the outcome of these transitions would involve designing synthetic organisms and synthetic ecological interactions that could push these endangered systems out of the critical boundaries. In this paper, we investigate the dynamics of the simplest mathematical models associated with four classes of ecological engineering designs, named Terraformation motifs (TMs). These TMs put in a nutshell different ecological strategies. In this context, some fundamental types of bifurcations pervade the systems' dynamics. Mutualistic interactions can enhance persistence of the systems by means of saddle-node bifurcations. The models without cooperative interactions show that ecosystems achieve restoration through transcritical bifurcations. Thus, our analysis of the models allows us to define the stability conditions and parameter domains where these TMs must work.

Spatial dynamics of synthetic microbial mutualists and their parasites.

A major force contributing to the emergence of novelty in nature is the presence of cooperative interactions, where two or more components of a system act in synergy, sometimes leading to higher-order, emergent phenomena. Within molecular evolution, the so called hypercycle defines the simplest model of an autocatalytic cycle, providing major theoretical insights on the evolution of cooperation in the early biosphere. These closed cooperative loops have also inspired our understanding of how catalytic loops appear in ecological systems. In both cases, hypercycle and ecological cooperative loops, the role played by space seems to be crucial for their stability and resilience against parasites. However, it is difficult to test these ideas in natural ecosystems, where time and spatial scales introduce considerable limitations. Here, we use engineered bacteria as a model system to a variety of environmental scenarios identifying trends that transcend the specific model system, such an enhanced genetic diversity in environments requiring mutualistic interactions. Interestingly, we show that improved environments can slow down mutualistic range expansions as a result of genetic drift effects preceding local resource depletion. Moreover, we show that a parasitic strain is excluded from the population during range expansions (which acknowledges a classical prediction). Nevertheless, environmental deterioration can reshape population interactions, this same strain becoming part of a three-species mutualistic web in scenarios in which the two-strain mutualism becomes non functional. The evolutionary and ecological implications for the design of synthetic ecosystems are outlined.

Spatial self-organization in hybrid models of multicellular adhesion.

Spatial self-organization emerges in distributed systems exhibiting local interactions when nonlinearities and the appropriate propagation of signals are at work. These kinds of phenomena can be modeled with different frameworks, typically cellular automata or reaction-diffusion systems. A different class of dynamical processes involves the correlated movement of agents over space, which can be mediated through chemotactic movement or minimization of cell-cell interaction energy. A classic example of the latter is given by the formation of spatially segregated assemblies when cells display differential adhesion. Here, we consider a new class of dynamical models, involving cell adhesion among two stochastically exchangeable cell states as a minimal model capable of exhibiting well-defined, ordered spatial patterns. Our results suggest that a whole space of pattern-forming rules is hosted by the combination of physical differential adhesion and the value of probabilities modulating cell phenotypic switching, showing that Turing-like patterns can be obtained without resorting to reaction-diffusion processes. If the model is expanded allowing cells to proliferate and die in an environment where diffusible nutrient and toxic waste are at play, different phases are observed, characterized by regularly spaced patterns. The analysis of the parameter space reveals that certain phases reach higher population levels than other modes of organization. A detailed exploration of the mean-field theory is also presented. Finally, we let populations of cells with different adhesion matrices compete for reproduction, showing that, in our model, structural organization can improve the fitness of a given cell population. The implications of these results for ecological and evolutionary models of pattern formation and the emergence of multicellularity are outlined.

Emergence of proto-organisms from bistable stochastic differentiation and adhesion.

The rise of multicellularity in the early evolution of life represents a major challenge for evolutionary biology. Guidance for finding answers has emerged from disparate fields, from phylogenetics to modelling and synthetic biology, but little is known about the potential origins of multicellular aggregates before genetic programmes took full control of developmental processes. Such aggregates should involve spatial organization of differentiated cells and the modification of flows and concentrations of metabolites within well-defined boundaries. Here, we show that, in an environment where limited nutrients and toxic metabolites are introduced, a population of cells capable of stochastic differentiation and differential adhesion can develop into multicellular aggregates with conflict mediation mechanisms and a complex internal structure. The morphospace of possible patterns is shown to be very rich, including proto-organisms that display a high degree of organizational complexity, far beyond simple heterogeneous populations of cells. Our findings reveal that there is a potentially enormous richness of organismal complexity between simple mixed cooperators and embodied living organisms.

A morphospace for synthetic organs and organoids: the possible and the actual.

Efforts in evolutionary developmental biology have shed light on how organs are developed and why evolution has selected some structures instead of others. These advances in the understanding of organogenesis along with the most recent techniques of organotypic cultures, tissue bioprinting and synthetic biology provide the tools to hack the physical and genetic constraints in organ development, thus opening new avenues for research in the form of completely designed or merely altered settings. Here we propose a unifying framework that connects the concept of morphospace (i.e. the space of possible structures) with synthetic biology and tissue engineering. We aim for a synthesis that incorporates our understanding of both evolutionary and architectural constraints and can be used as a guide for exploring alternative design principles to build artificial organs and organoids. We present a three-dimensional morphospace incorporating three key features associated to organ and organoid complexity. The axes of this space include the degree of complexity introduced by developmental mechanisms required to build the structure, its potential to store and react to information and the underlying physical state. We suggest that a large fraction of this space is empty, and that the void might offer clues for alternative ways of designing and even inventing new organs.

Synthetic collective intelligence.

Intelligent systems have emerged in our biosphere in different contexts and achieving different levels of complexity. The requirement of communication in a social context has been in all cases a determinant. The human brain, probably co-evolving with language, is an exceedingly successful example. Similarly, social insects complex collective decisions emerge from information exchanges between many agents. The difference is that such processing is obtained out of a limited individual cognitive power. Computational models and embodied versions using non-living systems, particularly involving robot swarms, have been used to explore the potentiality of collective intelligence. Here we suggest a novel approach to the problem grounded in the genetic engineering of unicellular systems, which can be modified in order to interact, store memories or adapt to external stimuli in collective ways. What we label as Synthetic Swarm Intelligence defines a parallel approach to the evolution of computation and swarm intelligence and allows to explore potential embodied scenarios for decision making at the microscale. Here, we consider several relevant examples of collective intelligence and their synthetic organism counterparts.

Synthetic circuit designs for earth terraformation.

BACKGROUND: Mounting evidence indicates that our planet might experience runaway effects associated to rising temperatures and ecosystem overexploitation, leading to catastrophic shifts on short time scales. Remediation scenarios capable of counterbalancing these effects involve geoengineering, sustainable practices and carbon sequestration, among others. None of these scenarios seems powerful enough to achieve the desired restoration of safe boundaries. PRESENTATION OF THE HYPOTHESIS: We hypothesize that synthetic organisms with the appropriate engineering design could be used to safely prevent declines in some stressed ecosystems and help improving carbon sequestration. Such schemes would include engineering mutualistic dependencies preventing undesired evolutionary processes. We hypothesize that some particular design principles introduce unescapable constraints to the engineered organisms that act as effective firewalls. TESTING THE HYPOTHESIS: Testing this designed organisms can be achieved by using controlled bioreactor models, with single and heterogeneous populations, and accurate computational models including different scales (from genetic constructs and metabolic pathways to population dynamics). IMPLICATIONS OF THE HYPOTHESIS: Our hypothesis heads towards a future anthropogenic action that should effectively act as Terraforming processes. It also implies a major challenge in the existing biosafety policies, since we suggest release of modified organisms as potentially necessary strategy for success.

MiR-2 family regulates insect metamorphosis by controlling the juvenile hormone signaling pathway.

In 2009 we reported that depletion of Dicer-1, the enzyme that catalyzes the final step of miRNA biosynthesis, prevents metamorphosis in Blattella germanica. However, the precise regulatory roles of miRNAs in the process have remained elusive. In the present work, we have observed that Dicer-1 depletion results in an increase of mRNA levels of Krüppel homolog 1 (Kr-h1), a juvenile hormone-dependent transcription factor that represses metamorphosis, and that depletion of Kr-h1 expression in Dicer-1 knockdown individuals rescues metamorphosis. We have also found that the 3'UTR of Kr-h1 mRNA contains a functional binding site for miR-2 family miRNAs (for miR-2, miR-13a, and miR-13b). These data suggest that metamorphosis impairment caused by Dicer-1 and miRNA depletion is due to a deregulation of Kr-h1 expression and that this deregulation is derived from a deficiency of miR-2 miRNAs. We corroborated this by treating the last nymphal instar of B. germanica with an miR-2 inhibitor, which impaired metamorphosis, and by treating Dicer-1-depleted individuals with an miR-2 mimic to allow nymphal-to-adult metamorphosis to proceed. Taken together, the data indicate that miR-2 miRNAs scavenge Kr-h1 transcripts when the transition from nymph to adult should be taking place, thus crucially contributing to the correct culmination of metamorphosis.

A bottom-up characterization of transfer functions for synthetic biology designs: lessons from enzymology.

Within the field of synthetic biology, a rational design of genetic parts should include a causal understanding of their input-output responses-the so-called transfer function-and how to tune them. However, a commonly adopted strategy is to fit data to Hill-shaped curves without considering the underlying molecular mechanisms. Here we provide a novel mathematical formalization that allows prediction of the global behavior of a synthetic device by considering the actual information from the involved biological parts. This is achieved by adopting an enzymology-like framework, where transfer functions are described in terms of their input affinity constant and maximal response. As a proof of concept, we characterize a set of Lux homoserine-lactone-inducible genetic devices with different levels of Lux receptor and signal molecule. Our model fits the experimental results and predicts the impact of the receptor's ribosome-binding site strength, as a tunable parameter that affects gene expression. The evolutionary implications are outlined.

Regulation of atrophin by both strands of the mir-8 precursor.

In Drosophila melanogaster, miR-8-3p regulates mRNA levels of atrophin, a factor involved in neuromotor coordination, and we found that Blattella germanica with suppressed atrophin showed motor problems. Bionformatic predictions and luciferase-reporter tests indicated that B. germanica atrophin mRNA contains target sites for miR-8-3p and miR-8-5p. Suppression of miR-8-3p or miR-8-5p appeared to increase atrophin mRNA. The effects of suppression of Argonaute (AGO) 1 or AGO2 expression on miR-8-3p and miR-8-5p suggested that miR-8-3-p might predominantly bind to AGO1, whereas miR-8-5p might bind to a moderate extent to both AGO1 and AGO2 in the respective RNA-induced silencing complexes (RISCs). We propose that the interplay of miR-8-3p, miR-8-5p, AGO1 and AGO2, maintain the appropriate levels of atrophin mRNA. This would be the first example of two strands of the same miRNA precursor regulating a single transcript.

A combined model of hepatic polyamine and sulfur amino acid metabolism to analyze S-adenosyl methionine availability.

Many molecular details remain to be uncovered concerning the regulation of polyamine metabolism. A previous model of mammalian polyamine metabolism showed that S-adenosyl methionine availability could play a key role in polyamine homeostasis. To get a deeper insight in this prediction, we have built a combined model by integration of the previously published polyamine model and one-carbon and glutathione metabolism model, published by different research groups. The combined model is robust and it is able to achieve physiological steady-state values, as well as to reproduce the predictions of the individual models. Furthermore, a transition between two versions of our model with new regulatory factors added properly simulates the switch in methionine adenosyl transferase isozymes occurring when the liver enters in proliferative conditions. The combined model is useful to support the previous prediction on the role of S-adenosyl methionine availability in polyamine homeostasis. Furthermore, it could be easily adapted to get deeper insights on the connections of polyamines with energy metabolism.

Exploring and challenging the network of angiogenesis.

Angiogenesis is one of the hallmarks of cancer and, as such, one of the alternative general targets for anticancer therapy. Since angiogenesis is a complex process involving a high number of interconnected components, a network approach would be a convenient systemic way to analyse responses to directed drug attacks. Herein we show that, although the angiogenic network is easily broken by short combinations of directed attacks, it still remains essentially functional by keeping the global patterns and local efficiency essentially unaltered after these attacks. This is a clear sign of its high robustness and resilience and stresses the need of directed, combined attacks for an effective blockade of the process. The results of this theoretical study could be relevant for the design of new antiangiogenic therapies and the selection of their targets.

When metabolism meets topology: Reconciling metabolite and reaction networks.

The search for a systems-level picture of metabolism as a web of molecular interactions provides a paradigmatic example of how the methods used to characterize a system can bias the interpretation of its functional meaning. Metabolic maps have been analyzed using novel techniques from network theory, revealing some non-trivial, functionally relevant properties. These include a small-world structure and hierarchical modularity. However, as discussed here, some of these properties might actually result from an inappropriate way of defining network interactions. Starting from the so-called bipartite organization of metabolism, where the two meaningful subsets (reactions and metabolites) are considered, most current works use only one of the subsets by means of so-called graph projections. Unfortunately, projected graphs often ignore relevant biological and chemical constraints, thus leading to statistical artifacts. Some of these drawbacks and alternative approaches need to be properly addressed.

Systems biology metabolic modeling assistant: an ontology-based tool for the integration of metabolic data in kinetic modeling.

SUMMARY: We present Systems Biology Metabolic Modeling Assistant (SBMM Assistant), a tool built using an ontology-based mediator, and designed to facilitate metabolic modeling through the integration of data from repositories that contain valuable metabolic information. This software can be used for the visualization, design and management of metabolic networks; selection, integration and storage of metabolic information; and as an assistant for kinetic modeling. AVAILABILITY: SBMM Assistant for academic use is freely available at http://www.sbmm.uma.es.

AMMO-Prot: amine system project 3D-model finder.

BACKGROUND: Amines are biogenic amino acid derivatives, which play pleiotropic and very important yet complex roles in animal physiology. For many other relevant biomolecules, biochemical and molecular data are being accumulated, which need to be integrated in order to be effective in the advance of biological knowledge in the field. For this purpose, a multidisciplinary group has started an ontology-based system named the Amine System Project (ASP) for which amine-related information is the validation bench. RESULTS: In this paper, we describe the Ontology-Based Mediator developed in the Amine System Project (http://asp.uma.es) using the infrastructure of Semantic Directories, and how this system has been used to solve a case related to amine metabolism-related protein structures. CONCLUSIONS: This infrastructure is used to publish and manage not only ontologies and their relationships, but also metadata relating to the resources committed with the ontologies. The system developed is available at http://asp.uma.es/WebMediator.

Homocysteine is a potent modulator of plasma membrane electron transport systems.

The deregulation of homocysteine metabolism leads to hyperhomocysteinemia, a condition described as an independent cardiovascular disease risk factor. Ubiquitous plasma membrane redox systems can play a dual pro-oxidant and anti-oxidant role in defense. In this study, we test the hypothesis that homocysteine, as a redox active compound, could modulate the endothelial plasma membrane redox system. We show that homocysteine behaves as a very potent stimulator of this activity. Furthermore, we show that this inducing effect is also produced on tumor cells and that it can be observed at both the activity and protein levels. On the other hand, homocysteine treatment decreases the activity of the specific ectocellular tumor NADH oxidase. Taken together, these results underscore a potential antitumoral action of homocysteine.

Mathematical modeling of polyamine metabolism in mammals.

Polyamines are considered as essential compounds in living cells, since they are involved in cell proliferation, transcription, and translation processes. Furthermore, polyamine homeostasis is necessary to cell survival, and its deregulation is involved in relevant processes, such as cancer and neurodegenerative disorders. Great efforts have been made to elucidate the nature of polyamine homeostasis, giving rise to relevant information concerning the behavior of the different components of polyamine metabolism, and a great amount of information has been generated. However, a complex regulation at transcriptional, translational, and metabolic levels as well as the strong relationship between polyamines and essential cell processes make it difficult to discriminate the role of polyamine regulation itself from the whole cell response when an experimental approach is given in vivo. To overcome this limitation, a bottom-up approach to model mathematically metabolic pathways could allow us to elucidate the systemic behavior from individual kinetic and molecular properties. In this paper, we propose a mathematical model of polyamine metabolism from kinetic constants and both metabolite and enzyme levels extracted from bibliographic sources. This model captures the tendencies observed in transgenic mice for the so-called key enzymes of polyamine metabolism, ornithine decarboxylase, S-adenosylmethionine decarboxylase and spermine spermidine N-acetyl transferase. Furthermore, the model shows a relevant role of S-adenosylmethionine and acetyl-CoA availability in polyamine homeostasis, which are not usually considered in systemic experimental studies.

Localization of StarD5 cholesterol binding protein.

Human StarD5 belongs to the StarD4 subfamily of START (for steroidogenic acute regulatory lipid transfer) domain proteins. We previously reported that StarD5 is located in the cytosolic fraction of human liver and binds cholesterol and 25-hydroxycholesterol. After overexpression of the gene encoding StarD5 in primary rat hepatocytes, free cholesterol accumulated in intracellular membranes. These findings suggested StarD5 to be a directional cytosolic sterol transporter. The objective of this study was to determine the localization of StarD5 in human liver. Western blot analysis confirmed StarD5's presence in the liver but not in human hepatocytes. Immunohistochemistry studies showed StarD5 localized within sinusoidal lining cells in the human liver and colocalized with CD68, a marker for Kupffer cells. Western blot analyses identified the presence of StarD5 in monocytes and macrophages as well as mast cells, basophils, and promyelocytic cells, but not in human hepatocytes, endothelial cells, fibroblasts, osteocytes, astrocytes, or brain tissue. Cell fractionation and immunocytochemistry studies on THP-1 macrophages localized StarD5 to the cytosol and supported an association with the Golgi. The presence of this cholesterol/25-hydroxycholesterol-binding protein in cells related to inflammatory processes provides new clues to the role of this protein in free sterol transport in the cells and in lipid-mediated atherogenesis.