Single-molecule modeling of mRNA degradation by miRNA: Lessons from data

Recent experimental results on the effect of miRNA on the decay of its target mRNA have been analyzed against a previously hypothesized single molecule degradation pathway. According to that hypothesis, the silencing complex (miRISC) first interacts with its target mRNA and then recruits the protein complexes associated with NOT1 and PAN3 to trigger deadenylation (and subsequent degradation) of the target mRNA. Our analysis of the experimental decay patterns allowed us to refine the structure of the degradation pathways at the single molecule level. Surprisingly, we found that if the previously hypothesized network was correct, only about 7% of the target mRNA would be regulated by the miRNA mechanism, which is inconsistent with the available knowledge. Based on systematic data analysis, we propose the alternative hypothesis that NOT1 interacts with miRISC before binding to the target mRNA. Moreover, we show that when miRISC binds alone to the target mRNA, the mRNA is degraded more slowly, probably through a deadenylation-independent pathway. The new biochemical pathway we propose both fits the data and paves the way for new experimental work to identify new interactions.Comment: It contains also the Supplementary Materials as appendix

Compositional modelling of signalling pathways in timed concurrent constraint programming

International audienceThe biological data regarding the signalling pathways often consider single pathways or a small number of them. We propose a methodology for composing this kind of data in a coherent framework, in order to be able to investigate a bigger number of signalling pathways. We specify a biological system by means of a set of stoichiometric-like equations resembling the essential features of molecular interactions. We represent these equations by a timed concurrent constraint (ntcc) language, which can deal with partial information and the time for a reaction to occur. We describe a freely available prototypical implementation of our framework

Verification of Spatial and Temporal Modalities in Biochemical Systems

AbstractBiochemical systems such as metabolic and signaling pathways tend to be arranged in a physical space: the product of one reaction must be in the right place to become the reactant for the subsequent reaction in the pathway. Moreover, in some cases, the behavior of the systems can depend on both, the location of the reactants as well as on the time needed for the reaction to occur. We address the problem of specifying and verifying properties of biochemical systems that exhibit both temporal and spatial modalities at the same time. For that, we use as specification language a fragment of intuitionistic linear logic with subexponentials (SELL). The subexponential signature allows us to capture the spatial relations among the different components of the system and the timed constraints for reactions to occur. We show that our framework is general enough to give a declarative semantics to P-Systems and we show that such logical characterization has a strong level of adequacy. Hence, derivations in SELL follow exactly the behavior of the modeled system

A flat process calculus for nested membrane interactions

The link-calculus has been recently proposed as a process calculus for representing interactions that are open (i.e. that the number of processes may vary), and multiparty (i.e. that may involve more than two processes). Here, we apply the link-calculus for expressing, possibly hierarchical and non dyadic, biological interactions. In particular, we provide a natural encoding of Cardelli's Brane calculus, a compartment-based calculus, introduced to model the behaviour of nested membranes. Notably, the link-calculus is at, but we can model membranes just as special processes taking part in the biological reaction. Moreover, we give evidence that the link-calculus allows one to directly model biological phenomena at the more appropriate level of abstraction

A Computational Approach to the Functional Screening of Genomes

Comparative genomics usually involves managing the functional aspects of genomes, by simply comparing gene-by-gene functions. Following this approach, Mushegian and Koonin proposed a hypothetical minimal genome, Minimal Gene Set (MGS), aiming for a possible oldest ancestor genome. They obtained MGS by comparing the genomes of two simple bacteria and eliminating duplicated or functionally identical genes. The authors raised the fundamental question of whether a hypothetical organism possessing MGS is able to live or not. We attacked this viability problem specifying in silico the metabolic pathways of the MGS-based prokaryote. We then performed a dynamic simulation of cellular metabolic activities in order to check whether the MGS-prokaryote reaches some equilibrium state and produces the necessary biomass. We assumed these two conditions to be necessary for a living organism. Our simulations clearly show that the MGS does not express an organism that is able to live. We then iteratively proceeded with functional replacements in order to obtain a genome composition that gives rise to equilibrium. We ruled out 76 of the original 254 genes in the MGS, because they resulted in duplication from a functional point of view. We also added seven genes not present in the MGS. These genes encode for enzymes involved in critical nodes of the metabolic network. These modifications led to a genome composed of 187 elements expressing a virtually living organism, Virtual Cell (ViCe), that exhibits homeostatic capabilities and produces biomass. Moreover, the steady-state distribution of the concentrations of virtual metabolites that resulted was similar to that experimentally measured in bacteria. We conclude then that ViCe is able to “live in silico.

Modelling non-Markovian dynamics in biochemical reactions

Biochemical reactions are often modelled as discrete-state continuous-time stochastic processes evolving as memoryless Markov processes. However, in some cases, biochemical systems exhibit non-Markovian dynamics. We propose here a methodology for building stochastic simulation algorithms which model more precisely non-Markovian processes in some specific situations. Our methodology is based on Constraint Programming and is implemented by using Gecode, a state-of-the-art framework for constraint solving

Lipid Metabolism Is Dysregulated before, during and after Pregnancy in a Mouse Model of Gestational Diabetes.

The aim of the current study was to test the hypothesis that maternal lipid metabolism was modulated during normal pregnancy and that these modulations are altered in gestational diabetes mellitus (GDM). We tested this hypothesis using an established mouse model of diet-induced obesity with pregnancy-associated loss of glucose tolerance and a novel lipid analysis tool, Lipid Traffic Analysis, that uses the temporal distribution of lipids to identify differences in the control of lipid metabolism through a time course. Our results suggest that the start of pregnancy is associated with several changes in lipid metabolism, including fewer variables associated with de novo lipogenesis and fewer PUFA-containing lipids in the circulation. Several of the changes in lipid metabolism in healthy pregnancies were less apparent or occurred later in dams who developed GDM. Some changes in maternal lipid metabolism in the obese-GDM group were so late as to only occur as the control dams' systems began to switch back towards the non-pregnant state. These results demonstrate that lipid metabolism is modulated in healthy pregnancy and the timing of these changes is altered in GDM pregnancies. These findings raise important questions about how lipid metabolism contributes to changes in metabolism during healthy pregnancies. Furthermore, as alterations in the lipidome are present before the loss of glucose tolerance, they could contribute to the development of GDM mechanistically

A mouse model of gestational diabetes shows dysregulated lipid metabolism post-weaning, after return to euglycaemia.

BACKGROUND: Gestational diabetes is associated with increased risk of type 2 diabetes mellitus and cardiovascular disease for the mother in the decade after delivery. However, the molecular mechanisms that drive these effects are unknown. Recent studies in humans have shown that lipid metabolism is dysregulated before diagnosis of and during gestational diabetes and we have shown previously that lipid metabolism is also altered in obese female mice before, during and after pregnancy. These observations led us to the hypothesis that this persistent dysregulation reflects an altered control of lipid distribution throughout the organism. METHODS: We tested this in post-weaning (PW) dams using our established mouse model of obese GDM (high fat, high sugar, obesogenic diet) and an updated purpose-built computational tool for plotting the distribution of lipid variables throughout the maternal system (Lipid Traffic Analysis v2.3). RESULTS: This network analysis showed that unlike hyperglycaemia, lipid distribution and traffic do not return to normal after pregnancy in obese mouse dams. A greater range of phosphatidylcholines was found throughout the lean compared to obese post-weaning dams. A range of triglycerides that were found in the hearts of lean post-weaning dams were only found in the livers of obese post-weaning dams and the abundance of odd-chain FA-containing lipids differed locally in the two groups. We have therefore shown that the control of lipid distribution changed for several metabolic pathways, with evidence for changes to the regulation of phospholipid biosynthesis and FA distribution, in a number of tissues. CONCLUSIONS: We conclude that the control of lipid metabolism is altered following an obese pregnancy. These results support the hypothesis that obese dams that developed GDM maintain dysregulated lipid metabolism after pregnancy even when glycaemia returned to normal, and that these alterations could contribute to the increased risk of later type 2 diabetes and cardiovascular disease

Massive upper gastrointestinal bleeding from a pancreatic pseudocyst rupture: a case report

INTRODUCTION: Bleeding from pancreatic pseudocyst's rupture into adjacent organs is a rare, but potentially fatal, complication of chronic pancreatitis requiring quick management. Timing of the rupture is unpredictable; early diagnosis and correct management is essential in preventing the bleeding. CASE PRESENTATION: We describe the case of a 53 years old male patient successfully treated with emergency surgery for massive hematemesis due to a rupture of a bleeding pseudocyst into the stomach. Patient underwent emergency laparotomy and suture of the bleeding vessel. At 5 years follow-up patient is in healthy condition. CONCLUSION: This case shows to surgeons that pancreatic pseudocyst cannot be managed strictly with one rule and prompt surgical treatment is mandatory in case of haemodinamic instability

Paternal nutritional programming of lipid metabolism is propagated through sperm and seminal plasma

Background: The paternal diet affects lipid metabolism in offspring for at least two generations through nutritional programming. However, we do not know how this is propagated to the offspring. Objectives: We tested the hypothesis that the changes in lipid metabolism that are driven by paternal diet are propagated through spermatozoa and not seminal plasma. Methods: We applied an updated, purpose-built computational network analysis tool to characterise control of lipid metabolism systemically (Lipid Traffic Analysis v2.3) on a known mouse model of paternal nutritional programming. Results: The analysis showed that the two possible routes for programming effects, the sperm (genes) and seminal plasma (influence on the uterine environment), both have a distinct effect on the offspring’s lipid metabolism. Further, the programming effects in offspring suggest that changes in lipid distribution are more important than alterations in lipid biosynthesis. Conclusions: These results show how the uterine environment and genes both affect lipid metabolism in offspring, enhancing our understanding of the link between parental diet and metabolism in offspring