Marco Scotti

Modeling cellular compartmentation in one‐carbon metabolism

Folate‐mediated one‐carbon metabolism (FOCM) is associated with risk for numerous pathological states including birth defects, cancers, and chronic diseases. Although the enzymes that constitute the biological pathways have been well described and their interdependency through the shared use of folate cofactors appreciated, the biological mechanisms underlying disease etiologies remain elusive. The FOCM network is highly sensitive to nutritional status of several B‐vitamins and numerous penetrant gene variants that alter network outputs, but current computational approaches do not fully capture the dynamics and stochastic noise of the system. Combining the stochastic approach with a rule‐based representation will help model the intrinsic noise displayed by FOCM, address the limited flexibility of standard simulation methods for coarse‐graining the FOCM‐associated biochemical processes, and manage the combinatorial complexity emerging from reactions within FOCM that would otherwise be intractable. WIREs Syst Biol Med 2013, 5:343–365. doi: 10.1002/wsbm.1209

A network analysis of cofactor-protein interactions for analyzing associations between human nutrition and diseases.

The involvement of vitamins and other micronutrients in intermediary metabolism was elucidated in the mid 1900’s at the level of individual biochemical reactions. Biochemical pathways remain the foundational knowledgebase for understanding how micronutrient adequacy modulates health in all life stages. Current daily recommended intakes were usually established on the basis of the association of a single nutrient to a single, most sensitive adverse effect and thus neglect interdependent and pleiotropic effects of micronutrients on biological systems. Hence, the understanding of the impact of overt or sub-clinical nutrient deficiencies on biological processes remains incomplete. Developing a more complete view of the role of micronutrients and their metabolic products in protein-mediated reactions is of importance. We thus integrated and represented cofactor-protein interaction data from multiple and diverse sources into a multi-layer network representation that links cofactors, cofactor-interacting proteins, biological processes, and diseases. Network representation of this information is a key feature of the present analysis and enables the integration of data from individual biochemical reactions and protein-protein interactions into a systems view, which may guide strategies for targeted nutritional interventions aimed at improving health and preventing diseases.

Model-based clustering reveals vitamin D dependent multi-centrality hubs in a network of vitamin-related proteins

BackgroundNutritional systems biology offers the potential for comprehensive predictions that account for all metabolic changes with the intricate biological organization and the multitudinous interactions between the cellular proteins. Protein-protein interaction (PPI) networks can be used for an integrative description of molecular processes. Although widely adopted in nutritional systems biology, these networks typically encompass a single category of functional interaction (i.e., metabolic, regulatory or signaling) or nutrient. Incorporating multiple nutrients and functional interaction categories under an integrated framework represents an informative approach for gaining system level insight on nutrient metabolism.ResultsWe constructed a multi-level PPI network starting from the interactions of 200 vitamin-related proteins. Its final size was 1,657 proteins, with 2,700 interactions. To characterize the role of the proteins we computed 6 centrality indices and applied model-based clustering. We detected a subgroup of 22 proteins that were highly central and significantly related to vitamin D. Immune system and cancer-related processes were strongly represented among these proteins. Clustering of the centralities revealed a degree of redundancy among the indices; a repeated analysis using subsets of the centralities performed well in identifying the original set of 22 most central proteins.ConclusionsHierarchical and model-based clustering revealed multi-centrality hubs in a vitamin PPI network and redundancies among the centrality indices. Vitamin D-related proteins were strongly represented among network hubs, highlighting the pervasive effects of this nutrient. Our integrated approach to network construction identified promiscuous transcription factors, cytokines and enzymes - primarily related to immune system and cancer processes - representing potential gatekeepers linking vitamin intake to disease.

Diversity of key players in the microbial ecosystems of the human body

Coexisting bacteria form various microbial communities in human body parts. In these ecosystems they interact in various ways and the properties of the interaction network can be related to the stability and functional diversity of the local bacterial community. In this study, we analyze the interaction network among bacterial OTUs in 11 locations of the human body. These belong to two major groups. One is the digestive system and the other is the female genital tract. In each local ecosystem we determine the key species, both the ones being in key positions in the interaction network and the ones that dominate by frequency. Beyond identifying the key players and discussing their biological relevance, we also quantify and compare the properties of the 11 networks. The interaction networks of the female genital system and the digestive system show totally different architecture. Both the topological properties and the identity of the key groups differ. Key groups represent four phyla of prokaryotes. Some groups appear in key positions in several locations, while others are assigned only to a single body part. The key groups of the digestive and the genital tracts are totally different.

Social and landscape effects on food webs: a multi-level network simulation model

One source of complexity in ecological systems is the hierarchical organization of parallel biological processes. Our ‘horizontal’ knowledge describing different levels is quite massive, but the understanding of their vertical interactions is very poor. We present a toy model linking social networks, food webs and a landscape graph. Horizontal processes refer to population, community and metacommunity dynamics, while vertical processes connect the three organizational levels. The model is stochastic and individual-based. We parametrized it by using reasonable empirical values found in the literature. Sensitivity analysis shows how the parameters describing the dynamics of a particular species (e.g., probability of social tie formation with conspecific individuals, or migration rate) can affect metapopulation size and spatial heterogeneity of all food web species. Changing the values of various parameters at any of the three levels have commensurable effects on the population size of all species. In contrast to the general intuition, community dynamics do not dominate population biology; social and landscape processes can trigger greater effects than food web interactions. More rapidly changing social relationships lead to a decrease in social network cohesion, thus impairing the feeding efficiency of consumers. In food webs, trophic specialization provides an advantage when it contributes to avoid competition, being detrimental otherwise. Highest migration rates result in a more heterogeneous metapopulation distribution of the generalist consumer, indirectly supporting its specialist competitor. We discuss conceptual and methodological aspects of the model, demonstrating the importance of an integrative view. We also emphasize the relevance of vertical connections, suggesting how such a modelling framework could support conservation biology. Further studies should focus on methods to approximate external pressures with changes in model parameters, thus allowing to characterize possible impacts on ecological systems.

Identifying marginal supplying countries of wood products via trade network analysis

PurposeThe consequential inventory modeling approach for life cycle assessment implies that an increase in the demand for a specific product is met by the marginal suppliers within the market. The identification of marginal suppliers is however complicated by difficulties in defining appropriate geographical market delimitations. In this study, an advanced system thinking approach is proposed to address this challenge in the identification of marginal supplying countries of wood products.MethodsGroups of countries which represent geographical markets are identified from trade data by using a network analysis-based clustering technique. Within these markets, marginal supplying countries are selected based on positive historical increments. The analysis covers 12 different products and all countries in the world using trade data for the period 1998–2013.Results and discussionGlobal indices allow differentiating how product-specific trade networks are separated into communities and how interconnected these networks are. Large differences between products and minor differences between trade years are observed. Communities identified for each product tend to overlap with existing geographical regions and seem thus realistic. By combining this information with product-specific production increment rankings, marginal supplying countries of wood products were identified.ConclusionsThe identified geographical market delimitation is a key for proper consequential life cycle assessment (LCA) inventory modeling in areas such as timber-based construction and biomass-based energy production. The method can in principle be applied to any product for which trade network data are available and ideally should be accompanied by a detailed analysis of technological constrains within the identified supplying country.

Integration of transcriptomic and genomic data suggests candidate mechanisms for APOE4-mediated pathogenic action in Alzheimer’s disease

Among the genetic factors known to increase the risk of late onset Alzheimer’s diseases (AD), the presence of the apolipoproteine e4 (APOE4) allele has been recognized as the one with the strongest effect. However, despite decades of research, the pathogenic role of APOE4 in Alzheimer’s disease has not been clearly elucidated yet. In order to investigate the pathogenic action of APOE4, we applied a systems biology approach to the analysis of transcriptomic and genomic data of APOE44 vs. APOE33 allele carriers affected by Alzheimer’s disease. Network analysis combined with a novel technique for biomarker computation allowed the identification of an alteration in aging-associated processes such as inflammation, oxidative stress and metabolic pathways, indicating that APOE4 possibly accelerates pathological processes physiologically induced by aging. Subsequent integration with genomic data indicates that the Notch pathway could be the nodal molecular mechanism altered in APOE44 allele carriers with Alzheimer’s disease. Interestingly, PSEN1 and APP, genes whose mutation are known to be linked to early onset Alzheimer’s disease, are closely linked to this pathway. In conclusion, APOE4 role on inflammation and oxidation through the Notch signaling pathway could be crucial in elucidating the risk factors of Alzheimer’s disease.

Nonlinear transcriptomic response to dietary fat intake in the small intestine of C57BL/6J mice

BackgroundA high caloric diet, in conjunction with low levels of physical activity, promotes obesity. Many studies are available regarding the relation between dietary saturated fats and the etiology of obesity, but most focus on liver, muscle and white adipose tissue. Furthermore, the majority of transcriptomic studies seek to identify linear effects of an external stimulus on gene expression, although such an assumption does not necessarily hold. Our work assesses the dose-dependent effects of dietary fat intake on differential gene expression in the proximal, middle and distal sections of the small intestine in C57BL/6J mice. Gene expression is analyzed in terms of either linear or nonlinear responses to fat intake.ResultsThe highest number of differentially expressed genes was observed in the middle section. In all intestine sections, most of the identified processes exhibited a linear response to increasing fat intake. The relative importance of logarithmic and exponential responses was higher in the proximal and distal sections, respectively. Functional enrichment analysis highlighted a constantly linear regulation of acute-phase response along the whole small intestine, with up-regulation of Serpina1b. The study of gene expression showed that exponential down-regulation of cholesterol transport in the middle section is coupled with logarithmic up-regulation of cholesterol homeostasis. A shift from linear to exponential response was observed in genes involved in the negative regulation of caspase activity, from middle to distal section (e.g., Birc5, up-regulated).ConclusionsThe transcriptomic signature associated with inflammatory processes preserved a linear response in the whole small intestine (e.g., up-regulation of Serpina1b). Processes related to cholesterol homeostasis were particularly active in the middle small intestine and only the highest fat intake down-regulated cholesterol transport and efflux (with a key role played by the down-regulation of ATP binding cassette transporters). Characterization of nonlinear patterns of gene expression triggered by different levels of dietary fat is an absolute novelty in intestinal studies. This approach helps identifying which processes are overloaded (i.e., positive, logarithmic regulation) or arrested (i.e., negative, exponential regulation) in response to excessive fat intake, and can shed light on the relationships linking lipid intake to obesity and its associated molecular disturbances.

Networks in Social Policy Problems: Index

1. Introduction M. Scotti and B. Vedres Part I. Information, Collaboration, Innovation: The Creative Power of Networks: 2. Dissemination of health information within social networks C. Dhanjal, S. Blanchemanche, S. Clemencon, A. Rona-Tas and F. Rossi 3. Scientific teams and networks change the face of knowledge creation S. Wuchty, J. Spiro, B. F. Jones and B. Uzzi 4. Structural folds: the innovative potential of overlapping groups B. Vedres and D. Stark 5. Team formation and performance on nanoHub: a network selection challenge in scientific communities D. Margolin, K. Ognyanova, M. Huang, Y. Huang and N. Contractor Part II. Influence, Capture, Corruption: Networks Perspectives on Policy Institutions: 6. Modes of coordination of collective action: what actors in policy making? M. Diani 7. Why skewed distributions of pay for executives is the cause of much grief: puzzles and few answers so far B. Kogut and J.-S. Yang 8. Networks of institutional capture: a case of business in the State apparatus E. Lazega and L. Mounier 9. The social and institutional structure of corruption: some typical network configurations of corruption transactions in Hungary Z. Szanto, I. J. Toth and S. Varga Part III. Crisis, Extinction, World System Change: Network Dynamics on a Large Scale: 10. How creative elements help the recovery of networks after crisis: lessons from biology A. Mihalik, A. S. Kaposi, I. A. Kovacs, T. Nanasi, R. Palotai, A. Rak, M. S. Szalay-Beko and P. Csermely 11. Networks and globalization policies D. R. White 12. Network science in ecology: the structure of ecological communities and the biodiversity question A. Bodini, S. Allesina and C. Bondavalli 13. Supply security in the European natural gas pipeline network M. Scotti and B. Vedres 14. Conclusions and outlook A.-L. Barabasi Index.

A hybrid stochastic model of folate-mediated one-carbon metabolism: Effect of the common C677T MTHFR variant on de novo thymidylate biosynthesis

Folate-mediated one-carbon metabolism (FOCM) is an interconnected network of metabolic pathways, including those required for the de novo synthesis of dTMP and purine nucleotides and for remethylation of homocysteine to methionine. Mouse models of folate-responsive neural tube defects (NTDs) indicate that impaired de novo thymidylate (dTMP) synthesis through changes in SHMT expression is causative in folate-responsive NTDs. We have created a hybrid computational model comprised of ordinary differential equations and stochastic simulation. We investigated whether the de novo dTMP synthesis pathway was sensitive to perturbations in FOCM that are known to be associated with human NTDs. This computational model shows that de novo dTMP synthesis is highly sensitive to the common MTHFR C677T polymorphism and that the effect of the polymorphism on FOCM is greater in folate deficiency. Computational simulations indicate that the MTHFR C677T polymorphism and folate deficiency interact to increase the stochastic behavior of the FOCM network, with the greatest instability observed for reactions catalyzed by serine hydroxymethyltransferase (SHMT). Furthermore, we show that de novo dTMP synthesis does not occur in the cytosol at rates sufficient for DNA replication, supporting empirical data indicating that impaired nuclear de novo dTMP synthesis results in uracil misincorporation into DNA.