"Be sustainable": EOSC-Life recommendations for implementation of FAIR principles in life science data handling.

The main goals and challenges for the life science communities in the Open Science framework are to increase reuse and sustainability of data resources, software tools, and workflows, especially in large-scale data-driven research and computational analyses. Here, we present key findings, procedures, effective measures and recommendations for generating and establishing sustainable life science resources based on the collaborative, cross-disciplinary work done within the EOSC-Life (European Open Science Cloud for Life Sciences) consortium. Bringing together 13 European life science research infrastructures, it has laid the foundation for an open, digital space to support biological and medical research. Using lessons learned from 27 selected projects, we describe the organisational, technical, financial and legal/ethical challenges that represent the main barriers to sustainability in the life sciences. We show how EOSC-Life provides a model for sustainable data management according to FAIR (findability, accessibility, interoperability, and reusability) principles, including solutions for sensitive- and industry-related resources, by means of cross-disciplinary training and best practices sharing. Finally, we illustrate how data harmonisation and collaborative work facilitate interoperability of tools, data, solutions and lead to a better understanding of concepts, semantics and functionalities in the life sciences.

Short tandem repeat profiling for the authentication of cancer stem-like cells.

Colorectal and glioblastoma cancer stem-like cells (CSCs) are essential for translational research. Cell line authentication by short tandem repeat (STR) profiling ensures reproducibility of results in oncology research. This technique enables to identify mislabeling or cross-contamination of cell lines. In our study, we provide a reference dataset for a panel of colorectal and glioblastoma CSCs that allows authentication. Each cell line was entered into the cell Line Integrated Molecular Authentication database 2.1 to be compared to the STR profiles of 4485 tumor cell lines. This article also provides clinical data of patients from whom CSCs arose and data on the parent tumor stage and mutations. STR profiles and information of our CSCs are also available in the Cellosaurus database (ExPASy) as identified by unique research resource identifier codes.

The 2017 Network Tools and Applications in Biology (NETTAB) workshop: aims, topics and outcomes.

The 17th International NETTAB workshop was held in Palermo, Italy, on October 16-18, 2017. The special topic for the meeting was "Methods, tools and platforms for Personalised Medicine in the Big Data Era", but the traditional topics of the meeting series were also included in the event. About 40 scientific contributions were presented, including four keynote lectures, five guest lectures, and many oral communications and posters. Also, three tutorials were organised before and after the workshop. Full papers from some of the best works presented in Palermo were submitted for this Supplement of BMC Bioinformatics. Here, we provide an overview of meeting aims and scope. We also shortly introduce selected papers that have been accepted for publication in this Supplement, for a complete presentation of the outcomes of the meeting.

Tools and data services registry: a community effort to document bioinformatics resources.

Life sciences are yielding huge data sets that underpin scientific discoveries fundamental to improvement in human health, agriculture and the environment. In support of these discoveries, a plethora of databases and tools are deployed, in technically complex and diverse implementations, across a spectrum of scientific disciplines. The corpus of documentation of these resources is fragmented across the Web, with much redundancy, and has lacked a common standard of information. The outcome is that scientists must often struggle to find, understand, compare and use the best resources for the task at hand.Here we present a community-driven curation effort, supported by ELIXIR-the European infrastructure for biological information-that aspires to a comprehensive and consistent registry of information about bioinformatics resources. The sustainable upkeep of this Tools and Data Services Registry is assured by a curation effort driven by and tailored to local needs, and shared amongst a network of engaged partners.As of November 2015, the registry includes 1785 resources, with depositions from 126 individual registrations including 52 institutional providers and 74 individuals. With community support, the registry can become a standard for dissemination of information about bioinformatics resources: we welcome everyone to join us in this common endeavour. The registry is freely available at https://bio.tools.

The joint NETTAB/Integrative Bioinformatics 2015 Meeting: aims, topics and outcomes.

The 15th International NETTAB workshop and the 11th Integrative Bioinformatics Symposium were held together in Bari, on October 14-16, 2016, as Joint NETTAB/IB 2015 Meeting. A special topic for the meeting was "Bioinformatics for ncRNA", but the traditional topics of both meetings series were also included in the event.About 60 scientific contributions were presented, including six keynote lectures, one special guest lecture, and many oral communications and posters. A "Two-Day Hands-on Tutorial" event was organised before the workshop.Selected full papers from some of the best works presented in Bari were submitted either to the Journal of Integrative Bioinformatics or to a purpose Call for a Supplement of BMC Bioinformatics.Here, we provide an overview of meeting aims and scope. We also shortly introduce selected papers that have been either accepted for publication in this Supplement or published in the Journal of Integrative Bioinformatics, for a more complete presentation of the outcomes of the meeting.

NETTAB 2014: From high-throughput structural bioinformatics to integrative systems biology.

The fourteenth NETTAB workshop, NETTAB 2014, was devoted to a range of disciplines going from structural bioinformatics, to proteomics and to integrative systems biology. The topics of the workshop were centred around bioinformatics methods, tools, applications, and perspectives for models, standards and management of high-throughput biological data, structural bioinformatics, functional proteomics, mass spectrometry, drug discovery, and systems biology.43 scientific contributions were presented at NETTAB 2014, including keynote, special guest and tutorial talks, oral communications, and posters. Full papers from some of the best contributions presented at the workshop were later submitted to a special Call for this Supplement.Here, we provide an overview of the workshop and introduce manuscripts that have been accepted for publication in this Supplement.

Geena 2, improved automated analysis of MALDI/TOF mass spectra.

BACKGROUND: Mass spectrometry (MS) is producing high volumes of data supporting oncological sciences, especially for translational research. Most of related elaborations can be carried out by combining existing tools at different levels, but little is currently available for the automation of the fundamental steps. For the analysis of MALDI/TOF spectra, a number of pre-processing steps are required, including joining of isotopic abundances for a given molecular species, normalization of signals against an internal standard, background noise removal, averaging multiple spectra from the same sample, and aligning spectra from different samples. In this paper, we present Geena 2, a public software tool for the automated execution of these pre-processing steps for MALDI/TOF spectra. RESULTS: Geena 2 has been developed in a Linux-Apache-MySQL-PHP web development environment, with scripts in PHP and Perl. Input and output are managed as simple formats that can be consumed by any database system and spreadsheet software. Input data may also be stored in a MySQL database. Processing methods are based on original heuristic algorithms which are introduced in the paper. Three simple and intuitive web interfaces are available: the Standard Search Interface, which allows a complete control over all parameters, the Bright Search Interface, which leaves to the user the possibility to tune parameters for alignment of spectra, and the Quick Search Interface, which limits the number of parameters to a minimum by using default values for the majority of parameters. Geena 2 has been utilized, in conjunction with a statistical analysis tool, in three published experimental works: a proteomic study on the effects of long-term cryopreservation on the low molecular weight fraction of serum proteome, and two retrospective serum proteomic studies, one on the risk of developing breat cancer in patients affected by gross cystic disease of the breast (GCDB) and the other for the identification of a predictor of breast cancer mortality following breast cancer surgery, whose results were validated by ELISA, a completely alternative method. CONCLUSIONS: Geena 2 is a public tool for the automated pre-processing of MS data originated by MALDI/TOF instruments, with a simple and intuitive web interface. It is now under active development for the inclusion of further filtering options and for the adoption of standard formats for MS spectra.

Preface: BITS2014, the annual meeting of the Italian Society of Bioinformatics.

This Preface introduces the content of the BioMed Central journal Supplements related to BITS2014 meeting, held in Rome, Italy, from the 26th to the 28th of February, 2014.

Matrix-assisted laser desorption/ionisation (MALDI) TOF analysis identifies serum angiotensin II concentrations as a strong predictor of all-cause and breast cancer (BCa)-specific mortality following breast surgery.

MALDI-TOF MS was used to recognise serum peptidome profiles predictive of mortality in women affected by early BCa. Mortality was analysed based on signal profiling, and appropriate statistics were used. The results indicate that four signals were increased in deceased patients compared with living patients. Three of the four signals were individually associated with all-cause mortality, but only one having mass/charge ratio (m/z) 1,046.49 was associated with BCa-specific mortality and was the only peak to maintain an independent prognostic role after multivariate analysis. Two groups exhibiting different mortality probabilities were identified after clustering patients based on the expression of the four peptides, but m/z 1,046.49 was exclusively expressed in the cluster exhibiting the worst mortality outcome, thus confirming the crucial value of this peptide. The specific role of this peak was confirmed by competing risk analysis. MS findings were validated by ELISA analysis after demonstrating that m/z 1,046.49 structurally corresponded to Angiotensin II (ATII). In fact, mortality results obtained after arbitrarily dividing patients according to an ATII serum value of 255 pg/ml (which corresponds to the 66(th) percentile value) were approximately comparable to those previously demonstrated when the same patients were analysed according to the expression of signal m/z 1,046.49. Similarly, ATII levels were specifically correlated with BCa-related deaths after competing risk analysis. In conclusion, ATII levels were increased in women who exhibited worse mortality outcomes, reinforcing the evidence that this peptide potentially significantly affects the natural history of early BCa. Our findings also confirm that MALDI-TOF MS is an efficient screening tool to identify novel tumour markers and that MS findings can be rapidly validated through less complex techniques, such as ELISA.

NETTAB 2013: Semantic, social, and mobile applications for bioinformatics and biomedical laboratories.

The thirteenth NETTAB workshop, NETTAB 2013, was devoted to semantic, social, and mobile applications for bioinformatics and biomedical laboratories. Topics included issues, methods, algorithms, and technologies for the design and development of tools and platforms able to provide semantic, social, and mobile applications supporting bioinformatics and the activities carried out in a biomedical laboratory. About 30 scientific contributions were presentedat NETTAB 2013, including keynote and tutorial talks, oral communications, and posters. Best contributions presented at the workshop were later submitted to a special Call for this Supplement. Here, we provide an overview of the workshop and introduce manuscripts that have been accepted for publication in this Supplement.

NETTAB 2012 on "Integrated Bio-Search".

The NETTAB 2012 workshop, held in Como on November 14-16, 2012, was devoted to "Integrated Bio-Search", that is to technologies, methods, architectures, systems and applications for searching, retrieving, integrating and analyzing data, information, and knowledge with the aim of answering complex bio-medical-molecular questions, i.e. some of the most challenging issues in bioinformatics today. It brought together about 80 researchers working in the field of Bioinformatics, Computational Biology, Biology, Computer Science and Engineering. More than 50 scientific contributions, including keynote and tutorial talks, oral communications, posters and software demonstrations, were presented at the workshop. This preface provides a brief overview of the workshop and shortly introduces the peer-reviewed manuscripts that were accepted for publication in this Supplement.

Integrated Bio-Search: challenges and trends for the integration, search and comprehensive processing of biological information.

Many efforts exist to design and implement approaches and tools for data capture, integration and analysis in the life sciences. Challenges are not only the heterogeneity, size and distribution of information sources, but also the danger of producing too many solutions for the same problem. Methodological, technological, infrastructural and social aspects appear to be essential for the development of a new generation of best practices and tools. In this paper, we analyse and discuss these aspects from different perspectives, by extending some of the ideas that arose during the NETTAB 2012 Workshop, making reference especially to the European context. First, relevance of using data and software models for the management and analysis of biological data is stressed. Second, some of the most relevant community achievements of the recent years, which should be taken as a starting point for future efforts in this research domain, are presented. Third, some of the main outstanding issues, challenges and trends are analysed. The challenges related to the tendency to fund and create large scale international research infrastructures and public-private partnerships in order to address the complex challenges of data intensive science are especially discussed. The needs and opportunities of Genomic Computing (the integration, search and display of genomic information at a very specific level, e.g. at the level of a single DNA region) are then considered. In the current data and network-driven era, social aspects can become crucial bottlenecks. How these may best be tackled to unleash the technical abilities for effective data integration and validation efforts is then discussed. Especially the apparent lack of incentives for already overwhelmed researchers appears to be a limitation for sharing information and knowledge with other scientists. We point out as well how the bioinformatics market is growing at an unprecedented speed due to the impact that new powerful in silico analysis promises to have on better diagnosis, prognosis, drug discovery and treatment, towards personalized medicine. An open business model for bioinformatics, which appears to be able to reduce undue duplication of efforts and support the increased reuse of valuable data sets, tools and platforms, is finally discussed.

MetaBase--the wiki-database of biological databases.

Biology is generating more data than ever. As a result, there is an ever increasing number of publicly available databases that analyse, integrate and summarize the available data, providing an invaluable resource for the biological community. As this trend continues, there is a pressing need to organize, catalogue and rate these resources, so that the information they contain can be most effectively exploited. MetaBase (MB) (http://MetaDatabase.Org) is a community-curated database containing more than 2000 commonly used biological databases. Each entry is structured using templates and can carry various user comments and annotations. Entries can be searched, listed, browsed or queried. The database was created using the same MediaWiki technology that powers Wikipedia, allowing users to contribute on many different levels. The initial release of MB was derived from the content of the 2007 Nucleic Acids Research (NAR) Database Issue. Since then, approximately 100 databases have been manually collected from the literature, and users have added information for over 240 databases. MB is synchronized annually with the static Molecular Biology Database Collection provided by NAR. To date, there have been 19 significant contributors to the project; each one is listed as an author here to highlight the community aspect of the project.

Bioinformatics in Italy: BITS 2012, the ninth annual meeting of the Italian Society of Bioinformatics.

The BITS2012 meeting, held in Catania on May 2-4, 2012, brought together almost 100 Italian researchers working in the field of Bioinformatics, as well as students in the same or related disciplines. About 90 original research works were presented either as oral communication or as posters, representing a landscape of Italian current research in bioinformatics. This preface provides a brief overview of the meeting and introduces the manuscripts that were accepted for publication in this supplement, after a strict and careful peer-review by an International board of referees.

Tools and collaborative environments for bioinformatics research.

Advanced research requires intensive interaction among a multitude of actors, often possessing different expertise and usually working at a distance from each other. The field of collaborative research aims to establish suitable models and technologies to properly support these interactions. In this article, we first present the reasons for an interest of Bioinformatics in this context by also suggesting some research domains that could benefit from collaborative research. We then review the principles and some of the most relevant applications of social networking, with a special attention to networks supporting scientific collaboration, by also highlighting some critical issues, such as identification of users and standardization of formats. We then introduce some systems for collaborative document creation, including wiki systems and tools for ontology development, and review some of the most interesting biological wikis. We also review the principles of Collaborative Development Environments for software and show some examples in Bioinformatics. Finally, we present the principles and some examples of Learning Management Systems. In conclusion, we try to devise some of the goals to be achieved in the short term for the exploitation of these technologies.

BNT162b2 Elicited an Efficient Cell-Mediated Response against SARS-CoV-2 in Kidney Transplant Recipients and Common Variable Immunodeficiency Patients.

SARS-CoV-2 vaccination is the standard of care for the prevention of COVID-19 disease. Although vaccination triggers both humoral and cellular immune response, COVID-19 vaccination efficacy is currently evaluated by measuring antibodies only, whereas adaptative cellular immunity is unexplored. Our aim is to test humoral and cell-mediated response after three doses of BNT162b vaccine in two cohorts of fragile patients: Common Variable Immunodeficiency (CVID) patients and Kidney Transplant Recipients (KTR) patients compared to healthy donors. We enrolled 10 healthy controls (HCs), 19 CVID patients and 17 KTR patients. HC BNT162b third dose had successfully mounted humoral immune response. A positive correlation between Anti-Spike Trimeric IgG concentration and neutralizing antibody titer was also observed. CVID and KTR groups showed a lower humoral immune response compared to HCs. IFN-γ release induced by epitopes of the Spike protein in stimulated CD4+ and CD8+ T cells was similar among vaccinated HC, CVID and KTR. Patients vaccinated and infected showed a more efficient humoral and cell-mediated response compared to only vaccinated patients. In conclusion, CVID and KTR patients had an efficient cell-mediated but not humoral response to SARS-CoV-2 vaccine, suggesting that the evaluation of T cell responses could be a more sensitive marker of immunization in these subjects.

Fraisinib: a calixpyrrole derivative reducing A549 cell-derived NSCLC tumor in vivo acts as a ligand of the glycine-tRNA synthase, a new molecular target in oncology.

Background and purpose: Lung cancer is the leading cause of death in both men and women, constituting a major public health problem worldwide. Non-small-cell lung cancer accounts for 85%-90% of all lung cancers. We propose a compound that successfully fights tumor growth in vivo by targeting the enzyme GARS1. Experimental approach: We present an in-depth investigation of the mechanism through which Fraisinib [meso-(p-acetamidophenyl)-calix(4)pyrrole] affects the human lung adenocarcinoma A549 cell line. In a xenografted model of non-small-cell lung cancer, Fraisinib was found to reduce tumor mass volume without affecting the vital parameters or body weight of mice. Through a computational approach, we uncovered that glycyl-tRNA synthetase is its molecular target. Differential proteomics analysis further confirmed that pathways regulated by Fraisinib are consistent with glycyl-tRNA synthetase inhibition. Key results: Fraisinib displays a strong anti-tumoral potential coupled with limited toxicity in mice. Glycyl-tRNA synthetase has been identified and validated as a protein target of this compound. By inhibiting GARS1, Fraisinib modulates different key biological processes involved in tumoral growth, aggressiveness, and invasiveness. Conclusion and implications: The overall results indicate that Fraisinib is a powerful inhibitor of non-small-cell lung cancer growth by exerting its action on the enzyme GARS1 while displaying marginal toxicity in animal models. Together with the proven ability of this compound to cross the blood-brain barrier, we can assess that Fraisinib can kill two birds with one stone: targeting the primary tumor and its metastases "in one shot." Taken together, we suggest that inhibiting GARS1 expression and/or GARS1 enzymatic activity may be innovative molecular targets for cancer treatment.

Bioinformatics in Italy: BITS2011, the Eighth Annual Meeting of the Italian Society of Bioinformatics.

The BITS2011 meeting, held in Pisa on June 20-22, 2011, brought together more than 120 Italian researchers working in the field of Bioinformatics, as well as students in Bioinformatics, Computational Biology, Biology, Computer Sciences, and Engineering, representing a landscape of Italian bioinformatics research.This preface provides a brief overview of the meeting and introduces the peer-reviewed manuscripts that were accepted for publication in this Supplement.

Towards linked open gene mutations data.

BACKGROUND: With the advent of high-throughput technologies, a great wealth of variation data is being produced. Such information may constitute the basis for correlation analyses between genotypes and phenotypes and, in the future, for personalized medicine. Several databases on gene variation exist, but this kind of information is still scarce in the Semantic Web framework. In this paper, we discuss issues related to the integration of mutation data in the Linked Open Data infrastructure, part of the Semantic Web framework. We present the development of a mapping from the IARC TP53 Mutation database to RDF and the implementation of servers publishing this data. METHODS: A version of the IARC TP53 Mutation database implemented in a relational database was used as first test set. Automatic mappings to RDF were first created by using D2RQ and later manually refined by introducing concepts and properties from domain vocabularies and ontologies, as well as links to Linked Open Data implementations of various systems of biomedical interest. Since D2RQ query performances are lower than those that can be achieved by using an RDF archive, generated data was also loaded into a dedicated system based on tools from the Jena software suite. RESULTS: We have implemented a D2RQ Server for TP53 mutation data, providing data on a subset of the IARC database, including gene variations, somatic mutations, and bibliographic references. The server allows to browse the RDF graph by using links both between classes and to external systems. An alternative interface offers improved performances for SPARQL queries. The resulting data can be explored by using any Semantic Web browser or application. CONCLUSIONS: This has been the first case of a mutation database exposed as Linked Data. A revised version of our prototype, including further concepts and IARC TP53 Mutation database data sets, is under development.The publication of variation information as Linked Data opens new perspectives: the exploitation of SPARQL searches on mutation data and other biological databases may support data retrieval which is presently not possible. Moreover, reasoning on integrated variation data may support discoveries towards personalized medicine.