322,874 research outputs found
Bioaccumulation and bioremediation modelling in Aquatic ecosystems: the Adriatic Sea case study
No full textUnderstanding the pathways of contaminant transfer within trophic networks is of paramount importance to weigh up forces driving ecological changes and to plan focused intervention strategies targeted to environmental\ud
conservation. The subject developed in this PhD dissertation aligns with this goal and encompasses the combination of different modelling approaches with experimental data to interpret the effects of bioaccumulation and bioremediation phenomena on species.\ud
Toxic agents adversely influence substance and energy fluxes at the ecosystem level affecting in turn the number of inter- and intra-specific interactions\ud
both at the community and population levels. Furthermore, the environmental stochasticity and the diversity of food webs along with the specificity of action of different bioaccumulative compounds greatly increase the\ud
complexity of this field of research. Current challenges in ecotoxicology focus on the need to find reliable predictive tools able to turn toxicity data of biota into powerful estimation methods and to asses the long-term effects of chemical exposure on species.\ud
In this context, predator-prey relationships are crucial to characterize the contamination patterns and to predict how chemicals transfer and accumulate within food webs. Food web members exhibit different levels of bioaccumulation in function of their trophic role, in a way that trophic links cannot be considered equal for all species in bioaccumulation phenomena.\ud
However, marine ecosystems are not just ensembles of macro-species, but complex multiscale networks. Microbial marine communities are metabolically involved in bioremediation processes and also represent an active compartment in the lower trophic levels of food webs. Thus, microbial degradation of persistent organic chemicals may play a key factor in changing the fate of these compounds within ecosystems and in reducing the contaminant uptake that leads to bioaccumulation in marine species.\ud
The work of research carried out during my PhD studies has been centred on the bioaccumulation and bioremediation modelling problems with specific interest on polychlorinated biphenyls (PCBs) contamination of the\ud
Adriatic food web. Notwithstanding a number of specific experimental studies on PCBs concentrations in different Adriatic species have been carried out over the last decades, to the best of our knowledge, a comprehensive\ud
PCBs bioaccumulation model for the Adriatic food web was still missing prior to the work presented in this thesis.\ud
The contributions of this PhD dissertation are structured by publication.\ud
Chapter 1 introduces the main content and includes an unpublished review of experimental PCBs concentration data in Adriatic species over the last two decades, along with an overview of the most important modelling approaches for bioaccumulation and bioremediation.\ud
In Chapter 2, we present a computational framework to model the bioaccumulation of organic chemicals in aquatic food webs, and to discover the toxic keystones, i.e. the species with a key role in the trophic transfer of\ud
contaminants. The approach is applied to reconstruct the first PCBs bioaccumulation model of the Adriatic food web, parametrized with a subset of the concentration data reviewed in Chapter 1. The framework integrates\ud
different modelling and analysis techniques, the first being the reconstruction of a trophic network from biomass data. Then, we use the estimated biomass flows and concentration data to derive the PCBs bioaccumulation\ud
network. Network reconstruction is performed using linear inverse modelling (LIM), an efficient technique for estimating food webs from empirical data. This step allows us to infer concentration values and contaminant\ud
flows for all species and remarkably, also for species with no input data associated. The estimated concentrations highlight the occurrence of PCBs\ud
biomagnification, which we show depending mainly on the trophic structure. The second main part of the framework is dedicated to the problem of identifying the toxic keystones, for which we propose the application of\ud
network analysis tools, typically employed in the trophic context. To this aim, we define a new network index, sensitivity centrality, able to capture not just direct and indirect effects in the PCBs network, but also the dynamics of bioaccumulation. Indeed, the index is based on the sensitivity analysis of a differential equation model derived from the bioaccumulation network. We compare sensitivity centrality with established network centrality indices, by evaluating the impact of successive species extinctions on global network properties, where such extinctions are performed following the importance ordering of the different indices. This analysis demonstrates that the introduced index can better identify the species with the highest impact on the total contaminant flows and on the efficiency of contaminant transport within the food web.\ud
In Chapter 3, we propose a novel computational framework of analysis to investigate multiscale effects of bioremediation processes at the ecosystem level. We integrate the bioaccumulation model presented in Chapter\ud
2 with the genome-scale metabolic network of Pseudomonas putida KT2440 (iJN746), which we extend to simulate the aerobic PCBs degradation under arbitrary scenarios of contaminant removal. We use a reaction-based ecological/microbial network representation by combining ecological and metabolic modelling techniques, namely LIM and flux balance analysis. In this way, we describe in a unique framework PCBs flows among species, metabolites concentrations and reactions fluxes in the microbial metabolism. We investigate the tradeoff between PCBs uptake and growth of P. putida at different oxygen levels, by using a bi-level flux balance analysis approach. We study the interdependence between PCBs and toluene uptake, which is a natural degradation pathways in P. putida, by performing a phenotypic phase plane analysis. We apply this framework to study how different\ud
bioremediation strategies can impact PCBs concentration in species, thus enabling an ecosystem level analysis. Finally, we evaluate also the effect of bioremediation on indices of species centrality in the PCBs bioaccumulation\ud
network.\ud
To sum up, the aims and contributions of this PhD thesis are:\ud
Provide a review of PCBs concentration data in the Adriatic ecosystem and of modelling methods for bioaccumulation and bioremediation.\ud
Reconstruct the first PCBs bioaccumulation model of the Adriatic food web and investigate species having a central role in the trophic transfer of contaminants.\ud
Integrate the Adriatic bioaccumulation model with a genome-scale metabolic model for PCBs biodegradation in order to enable multiscale ecosystem analyses.\ud
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References\ud
chapter 2: M. Taffi, N. Paoletti, P. Liò, S. Pucciarelli, and M. Marini. Bioaccumulation modelling and sensitivity analysis for discovering key players in contaminated food\ud
webs: The case study of PCBs in the Adriatic Sea. Ecological Modelling, 2014.\ud
chapter 3: M. Taffi, N. Paoletti, C. Angione, S. Pucciarelli, M. Marini, and P. Liò. Bioremediation\ud
in marine ecosystems: a computational study combining ecological modelling and flux balance analysis. Frontiers in Genetics, 5(319), 2014.\ud
2-phenylhydroxypropynyladenosine derivatives as high potent agonists at A(2B) adenosine receptor subtype
No full textAdenosine derivatives bearing in 2-position the (R,S)-phenylhydroxypropynyl chain were evaluated for their potency at human A(2B) adenosine receptor, stably transfected on CHO cells, on the basis that (R,S)-2-phenylhydroxy-propynyl-5'-N-ethylcarboxyamidoadenosine [(R,S)-PHPNECA] was found to be a good agonist at the A(2B) receptor subtype. Biological studies demonstrated that the presence of small alkyl groups in N-position of these molecules are well tolerated, whereas large groups abolished A(2B) potency. On the other hand, the presence of an ethyl group in the 4'-carboxamido function seems to be optimal, the (S)PHPNECA resulting the most potent agonist at A(2B) receptor reported so far
N(6)-alkyl-2-alkynyl derivatives of adenosine as potent and selective agonists at the human adenosine A(3) receptor and a starting point for searching A(2B) ligands
No full textA series of N-6-alkyl-2-alkynyl derivatives of adenosine (Ado) have been synthesized and evaluated for their affinity at human A(1), A(2A), and A(3) receptors and for their potency at A(2B) adenosine receptor subtypes. The corresponding 2-(1-alkynyl) derivatives of 5'-N-ethylcarboxamidoadenosine (NECA) and Ado are used as reference compounds. Binding studies demonstrated that the activities of 2-alkynylAdos were slightly increased for the adenosine A, receptor and slightly decreased for both A(3) and A(2B) subtypes compared to those of their corresponding NECA derivatives, whereas the A(2A) receptor affinities of the two series of nucleosides were similar. The presence of a methyl group on N-6 of the 2-alkynyladenosines, inducing an increase in affinity at the human A(3) receptor and a decrease at the other subtypes, resulted in an increase in A(3) selectivity. In particular, 2-phenylethynyl-N-6-methylAdo (8b) showed an A(3) affinity in the low nanomolar range (K-i(A(3)) = 3.4 nM), with a A(1)/A(3) and A(2A)/A(3) selectivity of about 500 and 2500, respectively. These findings motivated us to search for the preparation of new selective radioligands for the A(3) subtype; hence, a procedure to introduce a tritiated alkylamino group in these molecules was carried out. As far as the potency at the A(2B) receptor, the type of 2-alkynyl chain and the presence of the ethylcarboxamido group on the sugar seem to be very important; in fact, the (S)-2-phenylhydroxypropynylNECA [(S)-PHPNECA, 1e, EC50(A(2B)) = 0.22 muM] proved to be one of the most potent A(2B) agonist reported so far. On the other hand, the (S)-2-phenylhydroxypropynyl-N-6-ethylAdo (9e, EC50(A(2B)) = 0.73 muM) showed a significantly increase of potency at the A(2B) subtype in comparison with the N-6-methyl, N-6-isopropyl, and the unsubstituted adenosine derivatives, although it resulted in being less potent than (S)PHPNECA (le, EC50(A(2B)) = 0.22 muM). These observations suggest that the introduction of an ethyl group in the N-6-position and an ethylcarboxamido substituent in the 4'-position of (S)2-phenylhydroxypropynyladenosine could lead to a compound endowed with high potency at the A(2B) receptor
8-Bromo-9-etiladenine come tools per l’ottenimento di antagonisti selettivi per il recettore adenosinico A2B
No full textHuman cytidine deaminase: understanding the catalytic mechanism
No full textIn the absence of an experimentally elucidated three-dimensional structure of the human CDA, we built an homology model of this enzyme starting from the crystal structure of its E. coli homologous. Furthermore, we docked in the active site alternatively the substrate, the intermediate or the product. By means of molecular dynamics simulations, we determined the topology of the active site, identifying the amino acids involved in the catalytic mechanism, and outlining the central role played by E67
Purine and deazapurine nucleosides: synthetic approaches, molecular modeling and biological activity
No full textA number of ligands for the adenosine binding sites has been obtained by using nucleoside convergent and divergent synthesis. Most of our nucleosides have been synthesized by coupling 2,6-dichloropurine (1), 2,6-dichloro-1-deazapurine (2), 2,6-dichloro-3-deazapurine (3) with ribose, 2- and 3-deoxyribose and 2,3-dideoxyribose derivatives. The use of these versatile synthons allowed the introduction of various substituents in 2- and/or 6-positions. The glycosylation site and the anomeric configuration of the obtained nucleosides were assigned on the basis of spectroscopic studies and confirmed by molecular models. A series of potent adenosine receptor ligands has been obtained by using divergent approaches, mostly starting from guanosine. Substitutions in 2, 6, 8, and 5′ position of adenosine molecule led to ligands selective for the different adenosine receptor subtypes. Furthermore, we investigated the molecular bases of the different behavior of 2- and 8-alkynyl adenosines, by means of NMR experiments and molecular modeling studies. With docking experiments, we demonstrated that the two class of molecules should have different binding modes that explain their different degree of affinity and the shift of their activity from agonistic (2-substituted derivatives) to antagonistic (8-substituted derivatives)
A(2B) adenosine receptor agonists: synthesis and biological evaluation of 2-phenylhydroxypropynyladenosine and NECA derivatives
No full textIn the search for agonists for the elusive A(2B) adenosine receptor subtypes, 2-phenylhydroxypropynyl-5'-N-methylcarboxamido adenosine (PHPMECA, 14), 2-phenylhydroxypropynyl-5'-N-propylcarboxamido adenosine (PHPPECA, 15), and N-6-ethyl-2-phenylhydroxypropynyl-5'-N-ethylcarboxamidoadenosine (19) were synthesized on the basis that introduction of alkynyl chains in 2-position of adenosine derivatives resulted in reasonably good A2B potency compared to NECA [see N-6- ethyl-2-phenylhydroxypropynyl adenosine (5) EC50 = 1,700 nM and 2-phenylhydroxypropynyl-5'-N-ethylcarboxamido adenosine (PHPNECA, 8) EC50 = 1,100 nM, respectively]. Radioligand binding studies and adenylyl cyclase assays, performed with recently cloned human A(1), A(2A), A(2B), and A(3) adenosine receptors, showed that these modifications produced a decrease in potency at A(2B) receptor, as well as a general reduction in affinity at the other receptor subtypes. On the other hand, the contemporary presence of an ethyl substituent in N-6-position and of a 4'-ethylcarboxamido group in the same compounds led to (R,S)-N-6-ethyl -2-phenylhydroxypropynyl-5'-N-ethylcarboxamidoadenosine and (S)-N-6-ethyl-2-phenylhydroxypropynyl-5'-N-ethylcarboxamidoadenosine, which did not show the expected increase in potency at A(2B) subtype. Hence, (S)-2-phenylhydroxypropynyl-5'-N-ethylcarboxamidoadenosine [(S)-PHPNECA] with EC50 A(2B) = 220 nM remains the most potent agonist at A(2B) receptor reported so far
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