20 Oral Communications EMBnet.journal 18.B Rational design of organelle compartments in cells

In recent years there is a growing interest in researching on mitochondria, chloroplasts and other mitochondrion-like organelles (e.g. hydrogenosomes, mitosomes and apicoplasts) because of the integrate bio-search for comorbidities-related genes, pathway dysfunctions, the energy balance in aging, inflammation and disease, and the discovery of novel factors involved in organelle division, movement, signaling and adaptation to varying environmental and pathogenic conditions. Furthermore, there is an impressive amount of mitochondria and chloroplasts sequence data (thousands of mitochondrial sequences from many species have been sequenced) that hav

Multi-Target Analysis and Design of Mitochondrial Metabolism.

Analyzing and optimizing biological models is often identified as a research priority in biomedical engineering. An important feature of a model should be the ability to find the best condition in which an organism has to be grown in order to reach specific optimal output values chosen by the researcher. In this work, we take into account a mitochondrial model analyzed with flux-balance analysis. The optimal design and assessment of these models is achieved through single- and/or multi-objective optimization techniques driven by epsilon-dominance and identifiability analysis. Our optimization algorithm searches for the values of the flux rates that optimize multiple cellular functions simultaneously. The optimization of the fluxes of the metabolic network includes not only input fluxes, but also internal fluxes. A faster convergence process with robust candidate solutions is permitted by a relaxed Pareto dominance, regulating the granularity of the approximation of the desired Pareto front. We find that the maximum ATP production is linked to a total consumption of NADH, and reaching the maximum amount of NADH leads to an increasing request of NADH from the external environment. Furthermore, the identifiability analysis characterizes the type and the stage of three monogenic diseases. Finally, we propose a new methodology to extend any constraint-based model using protein abundances.PL has received funding from (FP7-Health-F5-2012) under grant agreement no. 305280 (MIMOmics). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.This is the final version of the article. It first appeared from PLoS via http://dx.doi.org/10.1371/journal.pone.013382

Computing with Metabolic Machines

If Turing were a first-year graduate student interested in computers, he would probably migrate into the field of computational biology. During his studies, he presented a work about a mathematical and computational model of the morphogenesis process, in which chemical substances react together. Moreover, a protein can be thought of as a computational element, i.e. a processing unit, able to transform an input into an output signal. Thus, in a biochemical pathway, an enzyme reads the amount of reactants (substrates) and converts them in products. In this work, we consider the biochemical pathway in unicellular organisms (e.g. bacteria) as a living computer, and we are able to program it in order to obtain desired outputs. The genome sequence is thought of as an executable code specified by a set of commands in a sort of ad-hoc low-level programming language. Each combination of genes is coded as a string of bits y ∈ {0, 1} L, each of which represents a gene set. By turning off a gene set, we turn off the chemical reaction associated with it. Through an optimal executable code stored in the “memory ” of bacteria, we are able to simultaneously maximise the concentration of two or more metabolites of interest. Finally, we use the Robustness Analysis and a new Sensitivity Analysis method to investigate both the fragility of the computation carried out by bacteria and the most important entities in the mathematical relations used to model them. 1 Introduction: From Turin

rational design of organelle compartments in cells

Motivation and Objectives In recent years there is a growing interest in researching on mitochondria, chloroplasts and other mitochondrion-like organelles (e.g. hydrogenosomes, mitosomes and apicoplasts) because of the integrate bio-search for comorbidities- related genes, pathway dysfunctions, the energy balance in aging, inflammation and disease, and the discovery of novel factors involved in organelle division, movement, signaling and adaptation to varying environmental and pathogenic conditions. Furthermore, there is an impressive amount of mitochondria and chloroplasts sequence data (thousands of mitochondrial sequences from many species have been sequenced) that have been used in the last ten years to derive the history of species. Notably, there are no examples of examined eukaryotes without a mitochondrion- related organelle (Shiflett and Johnson, 2010). Despite these research efforts, there is a lack of knowledge about the relationships between the organelles in a cell and its metabolism. We aim at investigating and comparing the complexity of these organelles through a common framework that includes single- and multi-objective optimization, robustness analysis and sensitivity analysis. The possibility of multiobjective- optimization in organelles such as the mitochondrion may be related to the different tasks of maximizing the ATP or the heat, or intermediate compounds of the Krebs cycle in order to provide input for biosynthetic pathways (e.g. the amino acids synthesis). Furthermore, rather than focusing only on networks of molecules, we think of the cell as an integrated system (Yoneda et al, 2009). Indeed, the systems biology approach, i.e. taking into account only molecular networks, misses the analysis of the organization provided by organelles. An organelle can be viewed as a functional organization of macromolecules working to accomplish essential cellular functions. Many conditions depend on a variety of environmental and other factors, and therefore cannot be fully investigated by conventional molecular-level approaches. Methods The cell contains many membrane-bound organelles, each specialized in one or more functions. External reactions can be thought of as links between organelles, since they involve metabolites found both in the cytoplasm and in the organelles. In our framework (Figure 1), we take into account complete models of the organelles in the cell, whose state space reflects its metabolism. The genetic algorithm underlying the optimization allows us to reach the optimal Pareto-front, i.e. to move the front towards the optimal point (e.g., maximum ATP and NADH), which is unfeasible if the two objective are negatively correlated with one another. The framework is implemented in MATLAB. Results and Discussion The genetic and the energy-converting networks of mitochondria and chloroplasts are descended, with little modification, from those of their ancestor bacteria. In this regard, we explore how the optimization and the Pareto front analysis can provide interesting insights into the evolutionary dynamics leading to the formation of organelle compartmentalization in the single- and multi-celled life. Furthermore, the sensitivity and robustness analyses can detect clusters of parameters corresponding to clusters of chemical reactions, which are often found in the cell and reflect the presence of different pathways or membrane-bound organelles. The interplay between optimization, sensitivity and robustness is useful not merely to reach the optimal configuration for the organelles, but also to conduct tentative analyses on their parameters. We have applied our framework to investigate models of organelles, e.g. mitochondria and chloroplasts. In the mitochondrial model (Bazil et al, 2010), we found that the most sensitive parameters are the Hexokinase max rate and the F1F0 ATP synthase activity. In the multi-objective optimization stage we analyzed the ATP-NADH Pareto front obtained with several calcium concentrations: if Ca2+ increases, we obtain an increase in NADH formation, while ATP remains constant; if Ca2+ drastically decreases, there is a lower ATP synthesis. Unexpectedly, with a slow decrease of Ca2+, both objectives are maximized. Our results highlight also that the natural mitochondrion is more robust than the optimized one, as it features a global robustness value of 26.94% and a local value of 9.00%. In the chloroplast model (Zhu et al, 2007), our framework detected RuBisCO and GAP dehydrogenase as the most sensitive enzymes of the C3 cycle. The Pareto fronts allowed us to find a trade-off between the maximization of the CO2 uptake rate and the minimization of the nitrogen consumption, with the aim of absorbing more CO2 while consuming less "leaf-fuel". RuBisCO and PGA kinase are the most robust enzymes. The functional optimization is not partitioned or delegated to the organelles. The selection is on the phenotype and acts on the whole cell's compartmentalized genomes. Indeed, it is the whole protozoan cell that competes with other protozoa. The fact that an organelle is kept during the evolution means that its contribution to the overall protozoan's fitness is not marginal, i.e., the presence of the organelle ensures some advantages over losing it. The contribution of each organelle is both to maximize the energy production and to coevolve with the other cell structures, so as to ensure the maximum fitness of the cell. The organelles in a cell play also a key role in the neuronal degeneration. In this regard, neurotransmitters are found in vesicles, i.e. tiny organelles that allow to respond to packets ("units") of neuronal chemical signaling. Following our framework and extending it, in the near future we plan to design, analyze and optimize the metabolism of systems composed of different species living and interacting in the same organism. In this project we have performed an in silico design that can explore the reaction network and seek in the search space the solutions that optimize two or more objectives. Therefore, our approach lies in the field of computational metabolic engineering. This kind of analysis could easily highlight the complementarity of different metabolic networks. For instance, mitochondria and chloroplasts are (usually) both found in plants, and are part of the same functional pipeline: starting from CO2, the photosynthesis in the chloroplast creates glucose that enters the mitochondria to create ATP. The model of the whole cell of a human pathogen (Karr et al, 2012) has opened new frontiers in this research field. The whole-cell model refers to the Mycoplasma genitalium and consists of 28 submodels accounting for all the biological functions of the cell. We have already applied our methodology to Flux Balance Analysis, Gene-Protein-Reaction associations, Ordinary Differential Equations (ODEs) and Differential Algebraic Equations (DAEs). Hence, our framework is suitable for general purpose or black-box analysis, enabling us to investigate not only the model of metabolism, but also the whole-cell model. Our final goal is to improve our methodology in order to tackle any BioCAD problem. In each Pareto front we have considered the single organelle, while in the cell there are usually many organelles that could differ for activity depending on their location in the cell. In a network of organelles, most of the reactions involve more than one organelle; an appropriate approach would be to build a Pareto front where each metabolite belongs to a different organelle in the network, linking with a set of Delay Differential Equations (DDEs). DDEs differ from ODEs in that they allow rates of change to depend on the state of the system at an earlier time. In organelle systems, DDEs could account for diffusion processes and maturation events. The integrated bio-search for a diseased, perturbed, misfunctional pathway often needs an accurate understanding of the relationships and interactions of that pathway with the organelle network system. The methodology proposed in our work could address most questions emerging in neurodegenerative and cancer disease investigation, which are focused on the interaction between organelle networks and cellular metabolism. References Bazil J N, Buzzard G T, Rundell A E (2010) Modeling mitochondrial bioenergetics with integrated volume dynamics. PLoS computational biology, 6(1):e1000632 Karr J R, Sanghvi J C, et al (2012) A Whole-Cell Computational Model Predicts Phenotype from Genotype. Cell, 150(2):389-401 Shiflett A and Johnson P J (2010) Mitochondrion-related organelles in parasitic eukaryotes. Annual review of microbiology, 64:409 Stelling J, et al (2004) Robustness of Cellular Functions. Cell, 118(6):675-685 Stracquadanio G and Nicosia G (2011) Computational energy-based redesign of robust proteins. Computers & chemical engineering, 35(3):464–473 Yoneda Y, et al (2009) Frontier biomedical science underlying organelle network biology, http://www.fbs.osaka-u.ac.jp/organelle-network/eng/greeting/greeting/ Zhu X G, de Sturler E, Long S P (2007) Optimizing the distribution of resources between enzymes of carbon metabolism can dramatically increase photosynthetic rate. Plant Physiology, 145:513–526 Note: Figures and tables are available in PDF version

Multi-objective optimization of genome-scale metabolic models: the case of ethanol production

Ethanol is among the largest fermentation product used worldwide, accounting for more than 90% of all biofuel produced in the last decade. However current production methods of ethanol are unable to meet the requirements of increasing global demand, because of low yields on glucose sources. In this work, we present an in silico multi-objective optimization and analyses of eight genome-scale metabolic networks for the overproduction of ethanol within the engineered cell. We introduce MOME (multi-objective metabolic engineering) algorithm, that models both gene knockouts and enzymes up and down regulation using the Redirector framework. In a multi-step approach, MOME tackles the multi-objective optimization of biomass and ethanol production in the engineered strain; and performs genetic design and clustering analyses on the optimization results. We find in silico E. coli Pareto optimal strains with a knockout cost of 14 characterized by an ethanol production up to 19.74mmolgDW−1h−1 (+832.88% with respect to wild-type) and biomass production of 0.02h−1 (−98.06% ). The analyses on E. coli highlighted a single knockout strategy producing 16.49mmolgDW−1h−1 (+679.29% ) ethanol, with biomass equals to 0.23h−1 (−77.45% ). We also discuss results obtained by applying MOME to metabolic models of: (i) S. aureus; (ii) S. enterica; (iii) Y. pestis; (iv) S. cerevisiae; (v) C. reinhardtii; (vi) Y. lipolytica. We finally present a set of simulations in which constrains over essential genes and minimum allowable biomass were included. A bound over the maximum allowable biomass was also added, along with other settings representing rich media compositions. In the same conditions the maximum improvement in ethanol production is +195.24%

L'"interpretazione secondo Costituzione" nella giurisprudenza. Crestomazia di decisioni giuridiche II Diritti reali- Obbligazioni. Autonomia negoziale - Responsabilità civile - Seconda edizione

Si tratta della raccolta aggiornata di casi giudiziari a fini didattici con particolare attenzione rivolta alle pronunce che, nel sistema del diritto civile, danno concretezza agli interessi esistenziali, sì da considerarli non come limiti esterni, ma quali valori normativi idonei ad incidere sulla funzione e, quindi, sulla natura degli istituti giuridici, anche patrimoniali. Emerge una raffigurazione della pratica dell'interpretazione "secondo Costituzione"

Introduzione

In questa raccolta di casi giudiziari a fini didattici particolare attenzione è rivolta alle pronunce che, nel sistema del diritto civile, danno concretezza agli interessi esistenziali, sì da considerarli non come limiti esterni, ma quali valori normativi idonei ad incidere sulla funzione e, quindi, sulla natura degli istituti anche patrimoniali del diritto civile. Emerge una raffigurazione della pratica dell'interpretazione «secondo costituzione». Le decisioni, organizzate secondo la tradizionale sistematica dell'esperienza didattica, sono precedute da un abstract che aiuta la lettura della sentenza e accompagnate da una nota di commento la quale evidenzia l'elaborazione dottrinale e giurisprudenziale relativa al tema trattato dalla decisione, al fine di storicizzare la ratio decidendi e permetterne una migliore comprensione. Non mancano annotazioni critiche a fronte di decisioni che, quantunque considerino le norme costituzionali come canoni ermeneutici, non colgono con pienezza le potenzialità di una interpretazione sistematica e assiologica

L'"interpretazione secondo Costituzione" nella giurisprudenza. Crestomazia di decisioni giuridiche, II, Diritti reali - Obbligazioni - Autonomia negoziale - Responsabilità civile

In questa raccolta di casi giudiziari a fini didattici particolare attenzione è stata rivolta alle pronunce che, nel sistema del diritto civile, danno concretezza agli interessi esistenziali, sì da considerarli non come limiti esterni, ma quali valori normativi idonei ad incidere sulla funzione e, quindi, sulla natura degli istituti anche patrimoniali del diritto civile. Emerge una raffigurazione della pratica dell’interpretazione «secondo costituzione». Le decisioni, organizzate secondo la tradizionale sistematica dell’esperienza didattica, sono precedute da un abstract che aiuta la lettura della sentenza e accompagnate da una nota di commento la quale evidenzia l’elaborazione dottrinale e giurisprudenziale relativa al tema trattato dalla decisione, al fine di storicizzare la ratio decidendi e permetterne una migliore comprensione. Non mancano annotazioni critiche a fronte di decisioni che, quantunque considerino le norme costituzionali come canoni ermeneutici, non colgono con pienezza le potenzialità di una interpretazione sistematica e assiologica