Lorenzo Dematte

Genome-wide transcriptional analysis of grapevine berry ripening reveals a set of genes similarly modulated during three seasons and the occurrence of an oxidative burst at vèraison

BackgroundGrapevine (Vitis species) is among the most important fruit crops in terms of cultivated area and economic impact. Despite this relevance, little is known about the transcriptional changes and the regulatory circuits underlying the biochemical and physical changes occurring during berry development.ResultsFruit ripening in the non-climacteric crop species Vitis vinifera L. has been investigated at the transcriptional level by the use of the Affymetrix Vitis GeneChip® which contains approximately 14,500 unigenes. Gene expression data obtained from berries sampled before and after véraison in three growing years, were analyzed to identify genes specifically involved in fruit ripening and to investigate seasonal influences on the process. From these analyses a core set of 1477 genes was found which was similarly modulated in all seasons. We were able to separate ripening specific isoforms within gene families and to identify ripening related genes which appeared strongly regulated also by the seasonal weather conditions. Transcripts annotation by Gene Ontology vocabulary revealed five overrepresented functional categories of which cell wall organization and biogenesis, carbohydrate and secondary metabolisms and stress response were specifically induced during the ripening phase, while photosynthesis was strongly repressed. About 19% of the core gene set was characterized by genes involved in regulatory processes, such as transcription factors and transcripts related to hormonal metabolism and signal transduction. Auxin, ethylene and light emerged as the main stimuli influencing berry development. In addition, an oxidative burst, previously not detected in grapevine, characterized by rapid accumulation of H2O2 starting from véraison and by the modulation of many ROS scavenging enzymes, was observed.ConclusionThe time-course gene expression analysis of grapevine berry development has identified the occurrence of two well distinct phases along the process. The pre-véraison phase represents a reprogramming stage of the cellular metabolism, characterized by the expression of numerous genes involved in hormonal signalling and transcriptional regulation. The post-véraison phase is characterized by the onset of a ripening-specialized metabolism responsible for the phenotypic traits of the ripe berry. Between the two phases, at véraison, an oxidative burst and the concurrent modulation of the anti-oxidative enzymatic network was observed. The large number of regulatory genes we have identified represents a powerful new resource for dissecting the mechanisms of fruit ripening control in non-climacteric plants.

GPU computing for systems biology

The development of detailed, coherent, models of complex biological systems is recognized as a key requirement for integrating the increasing amount of experimental data. In addition, in-silico simulation of bio-chemical models provides an easy way to test different experimental conditions, helping in the discovery of the dynamics that regulate biological systems. However, the computational power required by these simulations often exceeds that available on common desktop computers and thus expensive high performance computing solutions are required. An emerging alternative is represented by general-purpose scientific computing on graphics processing units (GPGPU), which offers the power of a small computer cluster at a cost of approximately

The Beta Workbench: a computational tool to study the dynamics of biological systems

400. Computing with a GPU requires the development of specific algorithms, since the programming paradigm substantially differs from traditional CPU-based computing. In this paper, we review some recent efforts in exploiting the processing power of GPUs for the simulation of biological systems.

The BlenX language: a tutorial

We introduce the Beta Workbench (BWB), a scalable tool built on top of the newly defined BlenX language to model, simulate and analyse biological systems. We show the features and the incremental modelling process supported by the BWB on a running example based on the mitogen-activated kinase pathway. Finally, we provide a comparison with related approaches and some hints for future extensions.

Modelling and simulation of biological processes in BlenX

This paper presents a new programming language, BlenX. BlenX is inspired to the process calculus Beta-binders and it is intended for modelling any system whose basic step of computation is an interaction between sub-components. The original development was thought for biological systems. Therefore this tutorial exemplifies BlenX features on biology-related systems.

On Parallel Stochastic Simulation of Diffusive Systems

We introduce a scalable framework built upon the BlenX language and inspired by the Beta-binders process calculus to model, simulate and analyse biological systems. We show the features of the Beta Workbench framework on a running example based on the mitogen-activated kinase pathway. We also discuss an incremental modelling process that allows us to scale up from pathway to network modelling and analysis. We finally provide a comparison with related approaches and some hints for future extensions of the framework.

Evolving BlenX programs to simulate the evolution of biological networks

The parallel simulation of biochemical reactions is a very interesting problem: biochemical systems are inherently parallel, yet the majority of the algorithms to simulate them, including the well-known and widespread Gillespie SSA, are strictly sequential. Here we investigate, in a general way, how to characterize the simulation of biochemical systems in terms of Discrete Event Simulation. We dissect their inherent parallelism in order both to exploit the work done in this area and to speed-up their simulation. We study the peculiar characteristics of discrete biological simulations in order to select the parallelization technique which provides the greater benefits, as well as to touch its limits. We then focus on reaction-diffusion systems: we design and implement an efficient parallel algorithm for simulating such systems that include both reactions between entities and movements throughout the space.

Smoldyn on Graphics Processing Units: Massively Parallel Brownian Dynamics Simulations

We present a formal approach to study the evolution of biological networks. We use the Beta Workbench and its BlenX language to model and simulate networks in connection with evolutionary algorithms. Mutations are done on the structure of BlenX programs and networks are selected at any generation by using a fitness function. The feasibility of the approach is illustrated with a simple example.

Programming Biology in BlenX

Space is a very important aspect in the simulation of biochemical systems; recently, the need for simulation algorithms able to cope with space is becoming more and more compelling. Complex and detailed models of biochemical systems need to deal with the movement of single molecules and particles, taking into consideration localized fluctuations, transportation phenomena, and diffusion. A common drawback of spatial models lies in their complexity: models can become very large, and their simulation could be time consuming, especially if we want to capture the systems behavior in a reliable way using stochastic methods in conjunction with a high spatial resolution. In order to deliver the promise done by systems biology to be able to understand a system as whole, we need to scale up the size of models we are able to simulate, moving from sequential to parallel simulation algorithms. In this paper, we analyze Smoldyn, a widely diffused algorithm for stochastic simulation of chemical reactions with spatial resolution and single molecule detail, and we propose an alternative, innovative implementation that exploits the parallelism of Graphics Processing Units (GPUs). The implementation executes the most computational demanding steps (computation of diffusion, unimolecular, and bimolecular reaction, as well as the most common cases of molecule-surface interaction) on the GPU, computing them in parallel on each molecule of the system. The implementation offers good speed-ups and real time, high quality graphics output.

Stochastic simulation of the spatio-temporal dynamics of reaction-diffusion systems: the case for the bicoid gradient.

We introduce a programming language called BlenX. It has been specifically designed and implemented to model and simulate biological systems and is strongly inspired to process calculi. We describe all the features of BlenX together with its supporting tools and show the application of the language on real case studies.