PINOT: an intuitive resource for integrating protein-protein interactions

The past decade has seen the rise of omics data, for the understanding of biological systems in health and disease. This wealth of data includes protein-protein interaction (PPI) derived from both low and high-throughput assays, which is curated into multiple databases that capture the extent of available information from the peer-reviewed literature. Although these curation efforts are extremely useful, reliably downloading and integrating PPI data from the variety of available repositories is challenging and time consuming. We here present a novel user-friendly web-resource called PINOT (Protein Interaction Network Online Tool; available at http://www.reading.ac.uk/bioinf/PINOT/PINOT_form.html) to optimise the collection and processing of PPI data from the IMEx consortium associated repositories (members and observers) and from WormBase for constructing, respectively, human and C. elegans PPI networks. Users submit a query containing a list of proteins of interest for which PINOT will mine PPIs. PPI data is downloaded, merged, quality checked, and confidence scored based on the number of distinct methods and publications in which each interaction has been reported. Examples of PINOT applications are provided to highlight the performance, the ease of use and the potential applications of this tool. PINOT is a tool that allows users to survey the literature, extracting PPI data for a list of proteins of interest. The comparison with analogous tools showed that PINOT was able to extract similar numbers of PPIs while incorporating a set of innovative features. PINOT processes both small and large queries, it downloads PPIs live through PSICQUIC and it applies quality control filters on the downloaded PPI annotations (i.e. removing the need of manual inspection by the user). PINOT provides the user with information on detection methods and publication history for each of the downloaded interaction data entry and provides results in a table format that can be easily further customised and/or directly uploaded in a network visualization software

The impact of radiotherapy late effects on quality of life in gynaecological cancer patients

The aims of this study were to assess changes in quality of life (QoL) scores in relation to radical radiotherapy for gynaecological cancer (before and after treatment up to 3 years), and to identify the effect that late treatment effects have on QoL. This was a prospective study involving 225 gynaecological cancer patients. A QoL instrument (European Organisation for the Research and Treatment of Cancer QLQ-C30) and late treatment effect questionnaire (Late Effects Normal Tissues – Subjective Objective Management Analysis) were completed before and after treatment (immediately after radiotherapy, 6 weeks, 12, 24 and 36 months after treatment). Most patients had acute physical symptoms and impaired functioning immediately after treatment. Levels of fatigue and diarrhoea only returned to those at pre-treatment assessment after 6 weeks. Patients with high treatment toxicity scores had lower global QoL scores. In conclusion, treatment with radiotherapy for gynaecological cancer has a negative effect on QoL, most apparent immediately after treatment. Certain late treatment effects have a negative effect on QoL for at least 2 years after radiotherapy. These treatment effects are centred on symptoms relating to the rectum and bowel, for example, diarrhoea, tenesmus and urgency. Future research will identify specific symptoms resulting from late treatment toxicity that have the greatest effect on QoL; therefore allowing effective management plans to be developed to reduce these symptoms and improve QoL in gynaecological cancer patients

Macro-level Modeling of the Response of C. elegans Reproduction to Chronic Heat Stress

A major goal of systems biology is to understand how organism-level behavior arises from a myriad of molecular interactions. Often this involves complex sets of rules describing interactions among a large number of components. As an alternative, we have developed a simple, macro-level model to describe how chronic temperature stress affects reproduction in C. elegans. Our approach uses fundamental engineering principles, together with a limited set of experimentally derived facts, and provides quantitatively accurate predictions of performance under a range of physiologically relevant conditions. We generated detailed time-resolved experimental data to evaluate the ability of our model to describe the dynamics of C. elegans reproduction. We find considerable heterogeneity in responses of individual animals to heat stress, which can be understood as modulation of a few processes and may represent a strategy for coping with the ever-changing environment. Our experimental results and model provide quantitative insight into the breakdown of a robust biological system under stress and suggest, surprisingly, that the behavior of complex biological systems may be determined by a small number of key components