Ten simple rules on how to develop a stakeholder engagement plan.

To make research responsible and research outcomes meaningful, it is necessary to communicate our research and to involve as many relevant stakeholders as possible, especially in application-oriented-including information and communications technology (ICT)-research. Nowadays, stakeholder engagement is of fundamental importance to project success and achieving the expected impact and is often mandatory in a third-party funding context. Ultimately, research and development can only be successful if people react positively to the results and benefits generated by a project. For the wider acceptance of research outcomes, it is therefore essential that the public is made aware of and has an opportunity to discuss the results of research undertaken through two-way communication (interpersonal communication) with researchers. Responsible Research and Innovation (RRI), an approach that anticipates and assesses potential implications and societal expectations regarding research and innovation, aims to foster inclusive and sustainable research and innovation. Research and innovation processes need to become more responsive and adaptive to these grand challenges. This implies, among other things, the introduction of broader foresight and impact assessments for new technologies beyond their anticipated market benefits and risks. Therefore, this article provides a structured workflow that explains "how to develop a stakeholder engagement plan" step by step.

Ten simple rules on how to write a standard operating procedure.

Research publications and data nowadays should be publicly available on the internet and, theoretically, usable for everyone to develop further research, products, or services. The long-term accessibility of research data is, therefore, fundamental in the economy of the research production process. However, the availability of data is not sufficient by itself, but also their quality must be verifiable. Measures to ensure reuse and reproducibility need to include the entire research life cycle, from the experimental design to the generation of data, quality control, statistical analysis, interpretation, and validation of the results. Hence, high-quality records, particularly for providing a string of documents for the verifiable origin of data, are essential elements that can act as a certificate for potential users (customers). These records also improve the traceability and transparency of data and processes, therefore, improving the reliability of results. Standards for data acquisition, analysis, and documentation have been fostered in the last decade driven by grassroot initiatives of researchers and organizations such as the Research Data Alliance (RDA). Nevertheless, what is still largely missing in the life science academic research are agreed procedures for complex routine research workflows. Here, well-crafted documentation like standard operating procedures (SOPs) offer clear direction and instructions specifically designed to avoid deviations as an absolute necessity for reproducibility. Therefore, this paper provides a standardized workflow that explains step by step how to write an SOP to be used as a starting point for appropriate research documentation.

The need for standardisation in life science research - an approach to excellence and trust.

Today, academic researchers benefit from the changes driven by digital technologies and the enormous growth of knowledge and data, on globalisation, enlargement of the scientific community, and the linkage between different scientific communities and the society. To fully benefit from this development, however, information needs to be shared openly and transparently. Digitalisation plays a major role here because it permeates all areas of business, science and society and is one of the key drivers for innovation and international cooperation. To address the resulting opportunities, the EU promotes the development and use of collaborative ways to produce and share knowledge and data as early as possible in the research process, but also to appropriately secure results with the European strategy for Open Science (OS). It is now widely recognised that making research results more accessible to all societal actors contributes to more effective and efficient science; it also serves as a boost for innovation in the public and private sectors. However  for research data to be findable, accessible, interoperable and reusable the use of standards is essential. At the metadata level, considerable efforts in standardisation have already been made (e.g. Data Management Plan and FAIR Principle etc.), whereas in context with the raw data these fundamental efforts are still fragmented and in some cases completely missing. The CHARME consortium, funded by the European Cooperation in Science and Technology (COST) Agency, has identified needs and gaps in the field of standardisation in the life sciences and also discussed potential hurdles for implementation of standards in current practice. Here, the authors suggest four measures in response to current challenges to ensure a high quality of life science research data and their re-usability for research and innovation.

A rapid approach for phenotype-screening and database independent detection of cSNP/protein polymorphism using mass accuracy precursor alignment.

The dynamics of a proteome can only be addressed with large-scale, high-throughput methods. To cope with the inherent complexity, techniques based on targeted quantification using proteotypic peptides are arising. This is an essential systems biology approach; however, for the exploratory discovery of unexpected markers, nontargeted detection of proteins, and protein modifications is indispensable. We present a rapid label-free shotgun proteomics approach that extracts relevant phenotype-specific peptide product ion spectra in an automated workflow without prior identification. These product ion spectra are subsequently sequenced with database search and de novo prediction algorithms. We analyzed six potato tuber cultivars grown on three plots of two geographically separated fields in Germany. For data mining about 1.5 million spectra from 107 analyses were aligned and statistically examined in approximately 1 day. Several cultivar-specific protein markers were detected. Based on de novo-sequencing a dominant protein polymorphism not detectable in the available EST-databases was assigned exclusively to a specific potato cultivar. The approach is applicable to organisms with unsequenced or incomplete genomes and to the automated extraction of relevant mass spectra that potentially cannot be identified by genome/EST-based search algorithms.

Starch content and yield increase as a result of altering adenylate pools in transgenic plants.

Starch represents the most important carbohydrate used for food and feed purposes. With the aim of increasing starch content, we decided to modulate the adenylate pool by changing the activity of the plastidial adenylate kinase in transgenic potato plants. As a result, we observed a substantial increase in the level of adenylates and, most importantly, an increase in the level of starch to 60% above that found in wild-type plants. In addition, concentrations of several amino acids were increased by a factor of 2-4. These results are particularly striking because this genetic manipulation also results in an increased tuber yield. The modulation of the plastidial adenylate kinase activity in transgenic plants therefore represents a potentially very useful strategy for increasing formation of major storage compounds in heterotrophic tissues of higher plants.

The Human Physiome: how standards, software and innovative service infrastructures are providing the building blocks to make it achievable.

Reconstructing and understanding the Human Physiome virtually is a complex mathematical problem, and a highly demanding computational challenge. Mathematical models spanning from the molecular level through to whole populations of individuals must be integrated, then personalized. This requires interoperability with multiple disparate and geographically separated data sources, and myriad computational software tools. Extracting and producing knowledge from such sources, even when the databases and software are readily available, is a challenging task. Despite the difficulties, researchers must frequently perform these tasks so that available knowledge can be continually integrated into the common framework required to realize the Human Physiome. Software and infrastructures that support the communities that generate these, together with their underlying standards to format, describe and interlink the corresponding data and computer models, are pivotal to the Human Physiome being realized. They provide the foundations for integrating, exchanging and re-using data and models efficiently, and correctly, while also supporting the dissemination of growing knowledge in these forms. In this paper, we explore the standards, software tooling, repositories and infrastructures that support this work, and detail what makes them vital to realizing the Human Physiome.

Strategies for structuring interdisciplinary education in Systems Biology: an European perspective.

Systems Biology is an approach to biology and medicine that has the potential to lead to a better understanding of how biological properties emerge from the interaction of genes, proteins, molecules, cells and organisms. The approach aims at elucidating how these interactions govern biological function by employing experimental data, mathematical models and computational simulations. As Systems Biology is inherently multidisciplinary, education within this field meets numerous hurdles including departmental barriers, availability of all required expertise locally, appropriate teaching material and example curricula. As university education at the Bachelor's level is traditionally built upon disciplinary degrees, we believe that the most effective way to implement education in Systems Biology would be at the Master's level, as it offers a more flexible framework. Our team of experts and active performers of Systems Biology education suggest here (i) a definition of the skills that students should acquire within a Master's programme in Systems Biology, (ii) a possible basic educational curriculum with flexibility to adjust to different application areas and local research strengths, (iii) a description of possible career paths for students who undergo such an education, (iv) conditions that should improve the recruitment of students to such programmes and (v) mechanisms for collaboration and excellence spreading among education professionals. With the growing interest of industry in applying Systems Biology approaches in their fields, a concerted action between academia and industry is needed to build this expertise. Here we present a reflection of the European situation and expertise, where most of the challenges we discuss are universal, anticipating that our suggestions will be useful internationally. We believe that one of the overriding goals of any Systems Biology education should be a student's ability to phrase and communicate research questions in such a manner that they can be solved by the integration of experiments and modelling, as well as to communicate and collaborate productively across different experimental and theoretical disciplines in research and development.

Future of medicine: models in predictive diagnostics and personalized medicine.

Molecular medicine is undergoing fundamental changes driving the whole area towards a revolution in modern medicine. The breakthrough was generated the fast-developing technologies in molecular biology since the first draft sequence of the human genome was published. The technological advances enabled the analysis of biological samples from cells and organs to whole organisms in a depth that was not possible before. These technologies are increasingly implemented in the medical and health care system to study diseases and refine diagnostics. As a consequence, the understanding of diseases and the health status of an individual patient is now based on an enormous amount of data that can only be interpreted in the context of the body as a whole. Systems biology as a new field in the life sciences develops new approaches for data integration and interpretation. Systems medicine as a specialized aspect of systems biology combines in an interdisciplinary approach all expertise necessary to decipher the human body in all its complexity. This created new challenges in the area of information and communication technologies to provide the infrastructure and technology needed to cope with the data flood that will accompany the next generation of medicine. The new initiative 'IT Future of Medicine' aims at driving this development even further and integrates not only molecular data (especially genomic information), but also anatomical, physiological, environmental, and lifestyle data in a predictive model approach-the 'virtual patient'-that will allow the clinician or the general practitioner to predict and anticipate the optimal treatment for the individual patient. The application of the virtual patient model will allow truly personalized medicine.

IT Future of Medicine: from molecular analysis to clinical diagnosis and improved treatment.

The IT Future of Medicine (ITFoM, http://www.itfom.eu/) initiative will produce computational models of individuals to enable the prediction of their future health risks, progression of diseases and selection and efficacy of treatments while minimising side effects. To be able to move our health care system to treat patients as individuals rather than as members of larger, divergent groups, the ITFoM initiative, proposes to integrate molecular, physiological and anatomical data of every person in 'virtual patient' models. The establishment of such 'virtual patient' models is now possible due to the enormous progress in analytical techniques, particularly in the '-omics' technology areas and in imaging, as well as in sensor technologies, but also due to the immense developments in the ICT field. As one of six Future and Emerging Technologies (FET) Flagship Pilot Projects funded by the European Commission, ITFoM with more than 150 academic and industrial partners from 34 countries, will foster the development in functional genomics and computer technologies to generate 'virtual patient' models to make them available for clinical application. The increase in the capacity of next generation sequencing systems will enable the high-throughput analysis of a large number of individuals generating huge amounts of genome, epigenome and transcriptome data, but making it feasible to apply deep sequencing in the clinic to characterise not only the patient's genome, but also individual samples, for example, from tumours. The genome profile will be integrated with proteome and metabolome information generated via new powerful chromatography, mass spectrometry and nuclear magnetic resonance techniques. The individualised model will not only enable the analysis of the current situation, but will allow the prediction of the response of the patient to different therapy options or intolerance for certain drugs.

Inhibition of de novo pyrimidine synthesis in growing potato tubers leads to a compensatory stimulation of the pyrimidine salvage pathway and a subsequent increase in biosynthetic performance.

Pyrimidine nucleotides are of general importance for many aspects of cell function, but their role in the regulation of biosynthetic processes is still unclear. In this study, we investigate the influence of a decreased expression of UMP synthase (UMPS), a key enzyme in the pathway of de novo pyrimidine synthesis, on biosynthetic processes in growing potato (Solanum tuberosum) tubers. Transgenic plants were generated expressing UMPS in the antisense orientation under the control of the tuber-specific patatin promoter. Lines were selected with markedly decreased expression of UMPS in the tubers. Decreased expression of UMPS restricted the use of externally supplied orotate for de novo pyrimidine synthesis in tuber tissue, whereas the uridine-salvaging pathway was stimulated. This shift in the pathways of UMP synthesis was accompanied by increased levels of tuber uridine nucleotides, increased fluxes of [(14)C]sucrose to starch and cell wall synthesis, and increased amounts of starch and cell wall components in the tubers, whereas there were no changes in uridine nucleotide levels in leaves. Decreased expression of UMPS in tubers led to an increase in transcript levels of carbamoylphosphate synthase, uridine kinase, and uracil phosphoribosyltransferase, the latter two encoding enzymes in the pyrimidine salvage pathways. Thus, the results show that antisense inhibition of the de novo pathway of pyrimidine synthesis leads to a compensatory stimulation of the less energy-consuming salvage pathways, probably via increased expression and activity of uridine kinase and uracil phosphoribosyltransferase. This results in increased uridine nucleotide pool levels in tubers and improved biosynthetic performance.

Heterologous expression of a ketohexokinase in potato plants leads to inhibited rates of photosynthesis, severe growth retardation and abnormal leaf development.

In the present paper we investigated the effect of heterologous expression of a rat liver ketohexokinase in potato (Solanum tuberosum L.) plants with the aim of investigating the role of fructose 1-phosphate in plant metabolism. Plants were generated that contained appreciable activity of ketohexokinase but did not accumulate fructose 1-phosphate. They were, however, characterised by a severe growth retardation and abnormal leaf development. Studies of (14)CO(2) assimilation and metabolism, and of the levels of photosynthetic pigments, revealed that these lines exhibited restricted photosynthesis. Despite this fact, the levels of starch and soluble sugars remained relatively constant. Analysis of intermediates of starch and sucrose biosynthesis revealed large increases in the triose phosphate and fructose 1,6-bisphosphate pools but relatively unaltered levels of inorganic phosphate and 3-phosphoglycerate, and these lines were also characterised by an accumulation of glyceraldehyde. The transformants neither displayed consistent changes in the activities of Calvin cycle enzymes nor in enzymes of sucrose synthesis but displayed a metabolic profile partially reminiscent of that brought about by end-product limitation, but most likely caused by an inhibition of photosynthesis brought about by the accumulation of glyceraldehyde. Analysis of the metabolite contents in lamina and vein fractions of the leaf, and of the enzymes of carbohydrate oxidation indicate that the phloem-enriched veins of ketohexokinase-expressing leaves tend toward hypoxia and indicate a problem of phloem transport.