Reconstruction of an in silico metabolic model of _Arabidopsis thaliana_ through database integration

The number of genome-scale metabolic models has been rising quickly in recent years, and the scope of their utilization encompasses a broad range of applications from metabolic engineering to biological discovery. However the reconstruction of such models remains an arduous process requiring a high level of human intervention. Their utilization is further hampered by the absence of standardized data and annotation formats and the lack of recognized quality and validation standards.

Plants provide a particularly rich range of perspectives for applications of metabolic modeling. We here report the first effort to the reconstruction of a genome-scale model of the metabolic network of the plant _Arabidopsis thaliana_, including over 2300 reactions and compounds. Our reconstruction was performed using a semi-automatic methodology based on the integration of two public genome-wide databases, significantly accelerating the process. Database entries were compared and integrated with each other, allowing us to resolve discrepancies and enhance the quality of the reconstruction. This process lead to the construction of three models based on different quality and validation standards, providing users with the possibility to choose the standard that is most appropriate for a given application. First, a _core metabolic model_ containing only consistent data provides a high quality model that was shown to be stoichiometrically consistent. Second, an _intermediate metabolic model_ attempts to fill gaps and provides better continuity. Third, a _complete metabolic model_ contains the full set of known metabolic reactions and compounds in _Arabidopsis thaliana_.

We provide an annotated SBML file of our core model to enable the maximum level of compatibility with existing tools and databases. We eventually discuss a series of principles to raise awareness of the need to develop coordinated efforts and common standards for the reconstruction of genome-scale metabolic models, with the aim of enabling their widespread diffusion, frequent update, maximum compatibility and convenience of use by the wider research community and industry

Inference of the genetic network regulating lateral root initiation in Arabidopsis thaliana

Regulation of gene expression is crucial for organism growth, and it is one of the challenges in Systems Biology to reconstruct the underlying regulatory biological networks from transcriptomic data. The formation of lateral roots in Arabidopsis thaliana is stimulated by a cascade of regulators of which only the interactions of its initial elements have been identified. Using simulated gene expression data with known network topology, we compare the performance of inference algorithms, based on different approaches, for which ready-to-use software is available. We show that their performance improves with the network size and the inclusion of mutants. We then analyse two sets of genes, whose activity is likely to be relevant to lateral root initiation in Arabidopsis, by integrating sequence analysis with the intersection of the results of the best performing methods on time series and mutants to infer their regulatory network. The methods applied capture known interactions between genes that are candidate regulators at early stages of development. The network inferred from genes significantly expressed during lateral root formation exhibits distinct scale-free, small world and hierarchical properties and the nodes with a high out-degree may warrant further investigation

Analyzing biological network parameters with CentiScaPe

Summary: The increasing availability of large network datasets along with the progresses in experimental high-throughput technologies have prompted the need for tools allowing easy integration of experimental data with data derived form network computational analysis. In order to enrich experimental data with network topological parameters, we have developed the Cytoscape plug-in CentiScaPe. The plug-in computes several network centrality parameters and allows the user to analyze existing relationships between experimental data provided by the users and node centrality values computed by the plug-in. CentiScaPe allows identifying network nodes that are relevant from both experimental and topological viewpoints. CentiScaPe also provides a Boolean logic-based tool that allows easy characterization of nodes whose topological relevance depends on more than one centrality. Finally, different graphic outputs and the included description of biological significance for each computed centrality facilitate the analysis by the end users not expert in graph theory, thus allowing easy node categorization and experimental prioritization

Characterization of the newly isolated lytic bacteriophages KTN6 and KT28 and their efficacy against Pseudomonas aeruginosa biofilm

We here describe two novel lytic phages, KT28 and KTN6, infecting Pseudomonas aeruginosa, isolated from a sewage sample from an irrigated field near Wroclaw, in Poland. Both viruses show characteristic features of Pbunalikevirus genus within the Myoviridae family with respect to shape and size of head/tail, as well as LPS host receptor recognition. Genome analysis confirmed the similarity to other PB1-related phages, ranging between 48 and 96%. Pseudomonas phage KT28 has a genome size of 66,381 bp and KTN6 of 65,994 bp. The latent period, burst size, stability and host range was determined for both viruses under standard laboratory conditions. Biofilm eradication efficacy was tested on peg-lid plate assay and PET membrane surface. Significant reduction of colony forming units was observed (70-90%) in 24 h to 72 h old Pseudomonas aeruginosa PAO1 biofilm cultures for both phages. Furthermore, a pyocyanin and pyoverdin reduction tests reveal that tested phages lowers the amount of both secreted dyes in 48-72 h old biofilms. Diffusion and goniometry experiments revealed the increase of diffusion rate through the biofilm matrix after phage application. These characteristics indicate these phages could be used to prevent Pseudomonas aeruginosa infections and biofilm formation. It was also shown, that PB1-related phage treatment of biofilm caused the emergence of stable phage-resistant mutants growing as small colony variants