Comparative genomics of Prunus-associated members of the Pseudomonas syringae species complex reveals traits supporting co-evolution and host adaptation

Related publication: https://doi.org/10.1186/s12864-019-5555-yMembers of the Pseudomonas syringae species complex cause symptoms that are ranging from leaf spots to cankers on a multitude of plant species, including some of the genus Prunus. To date, a total of two species of the P. syringae species complex and six different pathovars have been associated with diseases on Prunus spp., which were shown to belong to different phylogenetic units (phylogroups, PG) based on sequence similarity of housekeeping genes or whole genomes, suggesting that virulence to Prunus spp. may be the result of convergent pathoadaptation. In this study, a comparative genomics approach was used to determine genes significantly associated with strains isolated from Prunus spp. across a phylogeny of 97 strains belonging to the P. syringae species complex. Our study revealed the presence of a set of orthologous proteins which were significantly associated with strains isolated from Prunus spp. than in strains isolated from other hosts or from non-agricultural environments. Among them, the type III effector HopAY predicted to encode for a C58 cysteine protease was found to be highly associated with strains isolated from Prunus spp. and revealed patterns supporting co-evolution and host adaptation

Complete genome sequence of the cyanogenic phosphate-solubilizing Pseudomonas sp. strain CCOS 191 : a close relative of Pseudomonas mosseli

We sequenced the complete genome of the isolate Pseudomonas sp. CCOS 191. This strain is able to dissolve phosphate minerals and form cyanide. The genome sequence is used to establish the phylogenetic relationship of this species

The SIB Swiss Institute of Bioinformatics' resources: focus on curated databases

The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB's Bioinformatics resource portal ExPASy features over 150 resources, including UniProtKB/Swiss-Prot, ENZYME, PROSITE, neXtProt, STRING, UniCarbKB, SugarBindDB, SwissRegulon, EPD, arrayMap, Bgee, SWISS-MODEL Repository, OMA, OrthoDB and other databases, which are briefly described in this article

Comparative genomics of Prunus-associated members of the Pseudomonas syringae species complex reveals traits supporting co-evolution and host adaptation

Related publication: https://doi.org/10.1186/s12864-019-5555-yMembers of the Pseudomonas syringae species complex cause symptoms that are ranging from leaf spots to cankers on a multitude of plant species, including some of the genus Prunus. To date, a total of two species of the P. syringae species complex and six different pathovars have been associated with diseases on Prunus spp., which were shown to belong to different phylogenetic units (phylogroups, PG) based on sequence similarity of housekeeping genes or whole genomes, suggesting that virulence to Prunus spp. may be the result of convergent pathoadaptation. In this study, a comparative genomics approach was used to determine genes significantly associated with strains isolated from Prunus spp. across a phylogeny of 97 strains belonging to the P. syringae species complex. Our study revealed the presence of a set of orthologous proteins which were significantly associated with strains isolated from Prunus spp. than in strains isolated from other hosts or from non-agricultural environments. Among them, the type III effector HopAY predicted to encode for a C58 cysteine protease was found to be highly associated with strains isolated from Prunus spp. and revealed patterns supporting co-evolution and host adaptation

NIFTP-adjusted risk estimation of Bethesda thyroid cytology categories should consider the indication for FNA according to TIRADS.

Non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) was firstly described in 2016. Since NIFTP is thought a non-malignant tumor, the Bethesda system for thyroid cytology proposes two estimations of risk of malignancy of the diagnostic categories, one considering NIFTP as cancer and another one considering it as a benign neoplasm. The present study aimed to review NIFTPs in a single center, re-assess them across categories of three Thyroid Imaging Reporting and Data Systems (TIRADSs), and define the indication for biopsy according to the category-specific size cut-offs. The study period was from 2017 to 2023. The institutional database was searched for histologically proven NIFTPs with preoperative ultrasound images. NIFTPs were re-assessed according to the American College of Radiology (ACR), European (EU), and Korean (K) TIRADSs. The indication for biopsy was defined according to TIRADS category-specific size threshold. Twenty NIFTPs from 19 patients were included. The median size of the NIFTPs was 23 mm. According to ultrasound, 80-85% of NIFTPs were at low-intermediate risk and 5-15% at high risk without significant difference among the tree TIRADSs (p = 0.91). The indication for FNA, according to three TIRADSs, was found in 52-58% of cases with no significant difference among systems (p = 0.96). NIFTPs have heterogeneous presentation according to TIRADSs with very low indication rate for FNA

A methodology for enhanced flexibility of integrated assessment of policy impacts in agriculture

International audienc

A methodology for enhanced flexibility of integrated assessment in agriculture

Agriculture is interrelated with the socio-economic and natural environment and faces increasingly the problem of managing its multiple functions in a sustainable way. Growing emphasis is on adequate policies that can support both agriculture and sustainable development. Integrated Assessment and Modelling (IAM) can provide insight into the potential impacts of policy changes. An increasing number of Integrated Assessment (IA) models are being developed, but these are mainly monolithic and are targeted to answer specific problems. Approaches that allow flexible IA for a range of issues and functions are scarce. Recently, a methodology for policy support in agriculture has been developed that attempts to overcome some of the limitations of earlier IA models. The proposed framework (SEAMLESS-IF) integrates relationships and processes across disciplines and scales and combines quantitative analysis with qualitative judgments and experiences. It builds on the concept of systems analysis and attempts to enable flexible coupling of models and tools. The present paper aims to describe progress in improving flexibility of IAM achieved with the methodology developed for SEAMLESS-IF. A brief literature review identifying limitations in the flexibility of IAM is followed by a description of the progress achieved with SEAMLESS-IF. Two example applications are used to illustrate relevant capabilities of SEAMLESS-IF. The examples refer to (i) the impacts on European agriculture of changes in world trade regulations and (ii) regional impacts of the EU Nitrates Directive in combination with agro-management changes. We show that improving the flexibility of IAM requires flexibility in model linking but also a generic set up of all IA steps. This includes problem and scenario definition, the selection and specification of indicators and the indicator framework, the structuring of the database, and the visualization of results. Very important is the flexibility to integrate, select and link models, data and indicators depending on the application. Technical coupling and reusability of model components is greatly improved through adequate software architecture (SEAMLESS-IF uses OpenMI). The use of ontology strongly supports conceptual consistency of model linkages. However, the scientific basis for linking models across disciplines and scales is still weak and requires specific attention in future research. We conclude that the proposed framework significantly advances flexibility in IAM and that it is a good basis to further improve integrated modelling for policy impact assessment in agricultur