Getting your DUCs in a row - standardising the representation of Digital Use Conditions.

Improving patient care and advancing scientific discovery requires responsible sharing of research data, healthcare records, biosamples, and biomedical resources that must also respect applicable use conditions. Defining a standard to structure and manage these use conditions is a complex and challenging task. This is exemplified by a near unlimited range of asset types, a high variability of applicable conditions, and differing applications at the individual or collective level. Furthermore, the specifics and granularity required are likely to vary depending on the ultimate contexts of use. All these factors confound alignment of institutional missions, funding objectives, regulatory and technical requirements to facilitate effective sharing. The presented work highlights the complexity and diversity of the problem, reviews the current state of the art, and emphasises the need for a flexible and adaptable approach. We propose Digital Use Conditions (DUC) as a framework that addresses these needs by leveraging existing standards, striking a balance between expressiveness versus ambiguity, and considering the breadth of applicable information with their context of use.

Common conditions of use elements. Atomic concepts for consistent and effective information governance.

Myriad policy, ethical and legal considerations underpin the sharing of biological resources, implying the need for standardised and yet flexible ways to digitally represent diverse 'use conditions'. We report a core lexicon of terms that are atomic, non-directional 'concepts of use', called Common Conditions of use Elements. This work engaged biobanks and registries relevant to the European Joint Programme for Rare Diseases and aimed to produce a lexicon that would have generalised utility. Seventy-six concepts were initially identified from diverse real-world settings, and via iterative rounds of deliberation and user-testing these were optimised and condensed down to 20 items. To validate utility, support software and training information was provided to biobanks and registries who were asked to create Sharing Policy Profiles. This succeeded and involved adding standardised directionality and scope annotations to the employed terms. The addition of free-text parameters was also explored. The approach is now being adopted by several real-world projects, enabling this standard to evolve progressively into a universal basis for representing and managing conditions of use.

FAIR Header Reference genome: a TRUSTworthy standard.

The lack of interoperable data standards among reference genome data-sharing platforms inhibits cross-platform analysis while increasing the risk of data provenance loss. Here, we describe the FAIR bioHeaders Reference genome (FHR), a metadata standard guided by the principles of Findability, Accessibility, Interoperability and Reuse (FAIR) in addition to the principles of Transparency, Responsibility, User focus, Sustainability and Technology. The objective of FHR is to provide an extensive set of data serialisation methods and minimum data field requirements while still maintaining extensibility, flexibility and expressivity in an increasingly decentralised genomic data ecosystem. The effort needed to implement FHR is low; FHR's design philosophy ensures easy implementation while retaining the benefits gained from recording both machine and human-readable provenance.

EURO-NMD registry: federated FAIR infrastructure, innovative technologies and concepts of a patient-centred registry for rare neuromuscular disorders.

BACKGROUND: The EURO-NMD Registry collects data from all neuromuscular patients seen at EURO-NMD's expert centres. In-kind contributions from three patient organisations have ensured that the registry is patient-centred, meaningful, and impactful. The consenting process covers other uses, such as research, cohort finding and trial readiness. RESULTS: The registry has three-layered datasets, with European Commission-mandated data elements (EU-CDEs), a set of cross-neuromuscular data elements (NMD-CDEs) and a dataset of disease-specific data elements that function modularly (DS-DEs). The registry captures clinical, neuromuscular imaging, neuromuscular histopathology, biological and genetic data and patient-reported outcomes in a computer-interpretable format using selected ontologies and classifications. The EURO-NMD registry is connected to the EURO-NMD Registry Hub through an interoperability layer. The Hub provides an entry point to other neuromuscular registries that follow the FAIR data stewardship principles and enable GDPR-compliant information exchange. Four national or disease-specific patient registries are interoperable with the EURO-NMD Registry, allowing for federated analysis across these different resources. CONCLUSIONS: Collectively, the Registry Hub brings together data that are currently siloed and fragmented to improve healthcare and advance research for neuromuscular diseases.

DATA RESOURCES AND ANALYSES FAIR Header Reference genome: A TRUSTworthy standard.

The lack of interoperable data standards among reference genome data-sharing platforms inhibits cross-platform analysis while increasing the risk of data provenance loss. Here, we describe the FAIR-bioHeaders Reference genome (FHR), a metadata standard guided by the principles of Findability, Accessibility, Interoperability, and Reuse (FAIR) in addition to the principles of Transparency, Responsibility, User focus, Sustainability, and Technology (TRUST). The objective of FHR is to provide an extensive set of data serialisation methods and minimum data field requirements while still maintaining extensibility, flexibility, and expressivity in an increasingly decentralised genomic data ecosystem. The effort needed to implement FHR is low; FHR's design philosophy ensures easy implementation while retaining the benefits gained from recording both machine and human-readable provenance.

Testing the stress gradient hypothesis in soil bacterial communities associated with vegetation belts in the Andean Atacama Desert.

BACKGROUND: Soil microorganisms are in constant interaction with plants, and these interactions shape the composition of soil bacterial communities by modifying their environment. However, little is known about the relationship between microorganisms and native plants present in extreme environments that are not affected by human intervention. Using high-throughput sequencing in combination with random forest and co-occurrence network analyses, we compared soil bacterial communities inhabiting the rhizosphere surrounding soil (RSS) and the corresponding bulk soil (BS) of 21 native plant species organized into three vegetation belts along the altitudinal gradient (2400-4500 m a.s.l.) of the Talabre-Lejía transect (TLT) in the slopes of the Andes in the Atacama Desert. We assessed how each plant community influenced the taxa, potential functions, and ecological interactions of the soil bacterial communities in this extreme natural ecosystem. We tested the ability of the stress gradient hypothesis, which predicts that positive species interactions become increasingly important as stressful conditions increase, to explain the interactions among members of TLT soil microbial communities. RESULTS: Our comparison of RSS and BS compartments along the TLT provided evidence of plant-specific microbial community composition in the RSS and showed that bacterial communities modify their ecological interactions, in particular, their positive:negative connection ratios in the presence of plant roots at each vegetation belt. We also identified the taxa driving the transition of the BS to the RSS, which appear to be indicators of key host-microbial relationships in the rhizosphere of plants in response to different abiotic conditions. Finally, the potential functions of the bacterial communities also diverge between the BS and the RSS compartments, particularly in the extreme and harshest belts of the TLT. CONCLUSIONS: In this study, we identified taxa of bacterial communities that establish species-specific relationships with native plants and showed that over a gradient of changing abiotic conditions, these relationships may also be plant community specific. These findings also reveal that the interactions among members of the soil microbial communities do not support the stress gradient hypothesis. However, through the RSS compartment, each plant community appears to moderate the abiotic stress gradient and increase the efficiency of the soil microbial community, suggesting that positive interactions may be context dependent.

Towards FAIRification of sensitive and fragmented rare disease patient data: challenges and solutions in European reference network registries.

INTRODUCTION: Rare disease patient data are typically sensitive, present in multiple registries controlled by different custodians, and non-interoperable. Making these data Findable, Accessible, Interoperable, and Reusable (FAIR) for humans and machines at source enables federated discovery and analysis across data custodians. This facilitates accurate diagnosis, optimal clinical management, and personalised treatments. In Europe, twenty-four European Reference Networks (ERNs) work on rare disease registries in different clinical domains. The process and the implementation choices for making data FAIR ('FAIRification') differ among ERN registries. For example, registries use different software systems and are subject to different legal regulations. To support the ERNs in making informed decisions and to harmonise FAIRification, the FAIRification steward team was established to work as liaisons between ERNs and researchers from the European Joint Programme on Rare Diseases. RESULTS: The FAIRification steward team inventoried the FAIRification challenges of the ERN registries and proposed solutions collectively with involved stakeholders to address them. Ninety-eight FAIRification challenges from 24 ERNs' registries were collected and categorised into "training" (31), "community" (9), "modelling" (12), "implementation" (26), and "legal" (20). After curating and aggregating highly similar challenges, 41 unique FAIRification challenges remained. The two categories with the most challenges were "training" (15) and "implementation" (9), followed by "community" (7), and then "modelling" (5) and "legal" (5). To address all challenges, eleven types of solutions were proposed. Among them, the provision of guidelines and the organisation of training activities resolved the "training" challenges, which ranged from less-technical "coffee-rounds" to technical workshops, from informal FAIR Games to formal hackathons. Obtaining implementation support from technical experts was the solution type for tackling the "implementation" challenges. CONCLUSION: This work shows that a dedicated team of FAIR data stewards is an asset for harmonising the various processes of making data FAIR in a large organisation with multiple stakeholders. Additionally, multi-levelled training activities are required to accommodate the diverse needs of the ERNs. Finally, the lessons learned from the experience of the FAIRification steward team described in this paper may help to increase FAIR awareness and provide insights into FAIRification challenges and solutions of rare disease registries.

The malaria parasite chaperonin containing TCP-1 (CCT) complex: Data integration with other CCT proteomes.

The multi-subunit chaperonin containing TCP-1 (CCT) is an essential molecular chaperone that functions in the folding of key cellular proteins. This paper reviews the interactome of the eukaryotic chaperonin CCT and its primary clients, the ubiquitous cytoskeletal proteins, actin and tubulin. CCT interacts with other nascent proteins, especially the WD40 propeller proteins, and also assists in the assembly of several protein complexes. A new proteomic dataset is presented for CCT purified from the human malarial parasite, P. falciparum (PfCCT). The CCT8 subunit gene was C-terminally FLAG-tagged using Selection Linked Integration (SLI) and CCT complexes were extracted from infected human erythrocyte cultures synchronized for maximum expression levels of CCT at the trophozoite stage of the parasite's asexual life cycle. We analyze the new PfCCT proteome and incorporate it into our existing model of the CCT system, supported by accumulated data from biochemical and cell biological experiments in many eukaryotic species. Together with measurements of CCT mRNA, CCT protein subunit copy number and the post-translational and chemical modifications of the CCT subunits themselves, a cumulative picture is emerging of an essential molecular chaperone system sitting at the heart of eukaryotic cell growth control and cell cycle regulation.

The Indole-3-Acetamide-Induced Arabidopsis Transcription Factor MYB74 Decreases Plant Growth and Contributes to the Control of Osmotic Stress Responses.

The accumulation of the auxin precursor indole-3-acetamide (IAM) in the ami1 mutant has recently been reported to reduce plant growth and to trigger abiotic stress responses in Arabidopsis thaliana. The observed response includes the induction of abscisic acid (ABA) biosynthesis through the promotion of NCED3 expression. The mechanism by which plant growth is limited, however, remained largely unclear. Here, we investigated the transcriptional responses evoked by the exogenous application of IAM using comprehensive RNA-sequencing (RNA-seq) and reverse genetics approaches. The RNA-seq results highlighted the induction of a small number of genes, including the R2R3 MYB transcription factor genes MYB74 and MYB102. The two MYB factors are known to respond to various stress cues and to ABA. Consistent with a role as negative plant growth regulator, conditional MYB74 overexpressor lines showed a considerable growth reduction. RNA-seq analysis of MYB74 mutants indicated an association of MYB74 with responses to osmotic stress, water deprivation, and seed development, which further linked MYB74 with the observed ami1 osmotic stress and seed phenotype. Collectively, our findings point toward a role for MYB74 in plant growth control and in responses to abiotic stress stimuli.

Understanding the Relationships between Free Asparagine in Grain and Other Traits to Breed Low-Asparagine Wheat.

Since the discovery of acrylamide in food, and the identification of free asparagine as the key determinant of acrylamide concentration in wheat products, our understanding of how grain asparagine content is regulated has improved greatly. However, the targeted reduction in grain asparagine content has not been widely implemented in breeding programmes so far. Here we summarise how free asparagine concentration relates to other quality and agronomic traits and show that these relationships are unlikely to pose major issues for the breeding of low-asparagine wheat. We also outline the strategies that are possible for the breeding of low-asparagine wheat, using both natural and induced variation.

Semantic modelling of common data elements for rare disease registries, and a prototype workflow for their deployment over registry data.

BACKGROUND: The European Platform on Rare Disease Registration (EU RD Platform) aims to address the fragmentation of European rare disease (RD) patient data, scattered among hundreds of independent and non-coordinating registries, by establishing standards for integration and interoperability. The first practical output of this effort was a set of 16 Common Data Elements (CDEs) that should be implemented by all RD registries. Interoperability, however, requires decisions beyond data elements - including data models, formats, and semantics. Within the European Joint Programme on Rare Diseases (EJP RD), we aim to further the goals of the EU RD Platform by generating reusable RD semantic model templates that follow the FAIR Data Principles. RESULTS: Through a team-based iterative approach, we created semantically grounded models to represent each of the CDEs, using the SemanticScience Integrated Ontology as the core framework for representing the entities and their relationships. Within that framework, we mapped the concepts represented in the CDEs, and their possible values, into domain ontologies such as the Orphanet Rare Disease Ontology, Human Phenotype Ontology and National Cancer Institute Thesaurus. Finally, we created an exemplar, reusable ETL pipeline that we will be deploying over these non-coordinating data repositories to assist them in creating model-compliant FAIR data without requiring site-specific coding nor expertise in Linked Data or FAIR. CONCLUSIONS: Within the EJP RD project, we determined that creating reusable, expert-designed templates reduced or eliminated the requirement for our participating biomedical domain experts and rare disease data hosts to understand OWL semantics. This enabled them to publish highly expressive FAIR data using tools and approaches that were already familiar to them.

Conserved and distinct roles of H3K27me3 demethylases regulating flowering time in Brassica rapa.

Epigenetic regulation is necessary for optimal organism development and preservation of gene expression profiles in the cell. In plants, the trimethylation of histone H3 lysine 27 (H3K27me3) is a silencing epigenetic mark relevant for developmental transitions like flowering. The floral transition is a key agronomic trait; however, the epigenetic mechanisms of flowering time regulation in crops remain poorly understood. Here we study the Jumonji H3K27me3 demethylases BraA.REF6 and BraA.ELF6 in Brassica rapa. Phenotypic characterization of novel mutant lines and genome-wide H3K27me3 chromatin immunoprecipitation and transcriptomic analyses indicated that BraA.REF6 plays a greater role than BraA.ELF6 in fine-tuning H3K27me3 levels. In addition, we found that braA.elf6 mutants were early flowering due to high H3K27me3 levels at B. rapa homologs of the floral repressor FLC. Unlike mutations in Arabidopsis thaliana, braA.ref6 mutants were late flowering without altering the expression of B. rapa FLC genes. Remarkably, we found that BraA.REF6 regulated a number of gibberellic acid (GA) biosynthetic genes, including a homolog of GA1, and that GA-treatment complemented the late flowering mutant phenotype. This study increases our understanding of the epigenetic regulation of flowering time in B. rapa, highlighting conserved and distinct regulatory mechanisms between model and crop species.

Community-driven governance of FAIRness assessment: an open issue, an open discussion.

Although FAIR Research Data Principles are targeted at and implemented by different communities, research disciplines, and research stakeholders (data stewards, curators, etc.), there is no conclusive way to determine the level of FAIRness intended or required to make research artefacts (including, but not limited to, research data) Findable, Accessible, Interoperable, and Reusable. The FAIR Principles cover all types of digital objects, metadata, and infrastructures. However, they focus their narrative on data features that support their reusability. FAIR defines principles, not standards, and therefore they do not propose a mechanism to achieve the behaviours they describe in an attempt to be technology/implementation neutral. Various FAIR assessment metrics and tools have been designed to measure FAIRness. Unfortunately, the same digital objects assessed by different tools often exhibit widely different outcomes because of these independent interpretations of FAIR. This results in confusion among the publishers, the funders, and the users of digital research objects. Moreover, in the absence of a standard and transparent definition of what constitutes FAIR behaviours, there is a temptation to define existing approaches as being FAIR-compliant rather than having FAIR define the expected behaviours. This whitepaper identifies three high-level stakeholder categories -FAIR decision and policymakers, FAIR custodians, and FAIR practitioners - and provides examples outlining specific stakeholders' (hypothetical but anticipated) needs. It also examines possible models for governance based on the existing peer efforts, standardisation bodies, and other ways to acknowledge specifications and potential benefits. This whitepaper can serve as a starting point to foster an open discussion around FAIRness governance and the mechanism(s) that could be used to implement it, to be trusted, broadly representative, appropriately scoped, and sustainable. We invite engagement in this conversation in an open Google Group fair-assessment-governance@googlegroups.com.

RNAi suppression of xylan synthase genes in wheat starchy endosperm.

The xylan backbone of arabinoxylan (AX), the major cell wall polysaccharide in the wheat starchy endosperm, is synthesised by xylan synthase which is a complex of three subunits encoded by the GT43_1, GT43_2 and GT47_2 genes. RNAi knock-down of either GT43_1 or all three genes (triple lines) resulted in decreased AX measured by digestion with endoxylanase (to 33 and 34.9% of the controls) and by monosaccharide analysis (to 45.9% and 47.4% of the controls) with greater effects on the amount of water-extractable AX (to 20.6 and 19.9% of the controls). Both sets of RNAi lines also had greater decreases in the amounts of substituted oligosaccharides released by digestion of AX with endoxylanase than in fragments derived only from the xylan backbone. Although the GT43_1 and triple lines had similar effects on AX they did differ in their contents of soluble sugars (increased in triple only) and on grain size (decreased in triple only). Both sets of transgenic lines had decreased grain hardness, indicating effects on cell wall mechanics. These results, and previously published studies of RNAi suppression of GT43_2 and GT47_2 and of a triple mutant of GT43_2, are consistent with the model of xylan synthase comprising three subunits one of which (GT47_2) is responsible for catalysis with the other two subunits being required for correct functioning but indicate that separate xylan synthase complexes may be responsible for the synthesis of populations of AX which differ in their structure and solubility.

The TaCslA12 gene expressed in the wheat grain endosperm synthesizes wheat-like mannan when expressed in yeast and Arabidopsis.

Mannan is a class of cell wall polysaccharides widespread in the plant kingdom. Mannan structure and properties vary according to species and organ. The cell walls of cereal grains have been extensively studied due to their role in cereal processing and to their beneficial effect on human health as dietary fiber. Recently, we showed that mannan in wheat (Triticum aestivum) grain endosperm has a linear structure of ß-1,4-linked mannose residues. The aim of this work was to study the biosynthesis and function of wheat grain mannan. We showed that mannan is deposited in the endosperm early during grain development, and we identified candidate mannan biosynthetic genes expressed in the endosperm. The functional study in wheat was unsuccessful therefore our best candidate genes were expressed in heterologous systems. The endosperm-specificTaCslA12 gene expressed in Pichia pastoris and in an Arabidopsis thaliana mutant depleted in glucomannan led to the production of wheat-like linear mannan lacking glucose residues and with moderate acetylation. Therefore, this gene encodes a mannan synthase and is likely responsible for the synthesis of wheat endosperm mannan.

Endogenous indole-3-acetamide levels contribute to the crosstalk between auxin and abscisic acid, and trigger plant stress responses in Arabidopsis.

The evolutionary success of plants relies to a large extent on their extraordinary ability to adapt to changes in their environment. These adaptations require that plants balance their growth with their stress responses. Plant hormones are crucial mediators orchestrating the underlying adaptive processes. However, whether and how the growth-related hormone auxin and the stress-related hormones jasmonic acid, salicylic acid, and abscisic acid (ABA) are coordinated remains largely elusive. Here, we analyse the physiological role of AMIDASE 1 (AMI1) in Arabidopsis plant growth and its possible connection to plant adaptations to abiotic stresses. AMI1 contributes to cellular auxin homeostasis by catalysing the conversion of indole-acetamide into the major plant auxin indole-3-acetic acid. Functional impairment of AMI1 increases the plant's stress status rendering mutant plants more susceptible to abiotic stresses. Transcriptomic analysis of ami1 mutants disclosed the reprogramming of a considerable number of stress-related genes, including jasmonic acid and ABA biosynthesis genes. The ami1 mutants exhibit only moderately repressed growth but an enhanced ABA accumulation, which suggests a role for AMI1 in the crosstalk between auxin and ABA. Altogether, our results suggest that AMI1 is involved in coordinating the trade-off between plant growth and stress responses, balancing auxin and ABA homeostasis.

Predicting microbiomes through a deep latent space.

MOTIVATION: Microbial communities influence their environment by modifying the availability of compounds, such as nutrients or chemical elicitors. Knowing the microbial composition of a site is therefore relevant to improve productivity or health. However, sequencing facilities are not always available, or may be prohibitively expensive in some cases. Thus, it would be desirable to computationally predict the microbial composition from more accessible, easily-measured features. RESULTS: Integrating deep learning techniques with microbiome data, we propose an artificial neural network architecture based on heterogeneous autoencoders to condense the long vector of microbial abundance values into a deep latent space representation. Then, we design a model to predict the deep latent space and, consequently, to predict the complete microbial composition using environmental features as input. The performance of our system is examined using the rhizosphere microbiome of Maize. We reconstruct the microbial composition (717 taxa) from the deep latent space (10 values) with high fidelity (>0.9 Pearson correlation). We then successfully predict microbial composition from environmental variables, such as plant age, temperature or precipitation (0.73 Pearson correlation, 0.42 Bray-Curtis). We extend this to predict microbiome composition under hypothetical scenarios, such as future climate change conditions. Finally, via transfer learning, we predict microbial composition in a distinct scenario with only 100 sequences, and distinct environmental features. We propose that our deep latent space may assist microbiome-engineering strategies when technical or financial resources are limited, through predicting current or future microbiome compositions. AVAILABILITY AND IMPLEMENTATION: Software, results and data are available at https://github.com/jorgemf/DeepLatentMicrobiome. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Data-driven classification of the certainty of scholarly assertions.

The grammatical structures scholars use to express their assertions are intended to convey various degrees of certainty or speculation. Prior studies have suggested a variety of categorization systems for scholarly certainty; however, these have not been objectively tested for their validity, particularly with respect to representing the interpretation by the reader, rather than the intention of the author. In this study, we use a series of questionnaires to determine how researchers classify various scholarly assertions, using three distinct certainty classification systems. We find that there are three distinct categories of certainty along a spectrum from high to low. We show that these categories can be detected in an automated manner, using a machine learning model, with a cross-validation accuracy of 89.2% relative to an author-annotated corpus, and 82.2% accuracy against a publicly-annotated corpus. This finding provides an opportunity for contextual metadata related to certainty to be captured as a part of text-mining pipelines, which currently miss these subtle linguistic cues. We provide an exemplar machine-accessible representation-a Nanopublication-where certainty category is embedded as metadata in a formal, ontology-based manner within text-mined scholarly assertions.

A Biosynthetic Platform for Antimalarial Drug Discovery.

Advances in synthetic biology have enabled the production of a variety of compounds using bacteria as a vehicle for complex compound biosynthesis. Violacein, a naturally occurring indole pigment with antibiotic properties, can be biosynthetically engineered in Escherichia coli expressing its nonnative synthesis pathway. To explore whether this synthetic biosynthesis platform could be used for drug discovery, here we have screened bacterially derived violacein against the main causative agent of human malaria, Plasmodium falciparum We show the antiparasitic activity of bacterially derived violacein against the P. falciparum 3D7 laboratory reference strain as well as drug-sensitive and -resistant patient isolates, confirming the potential utility of this drug as an antimalarial agent. We then screen a biosynthetic series of violacein derivatives against P. falciparum growth. The varied activity of each derivative against asexual parasite growth points to the need to further develop violacein as an antimalarial. Towards defining its mode of action, we show that biosynthetic violacein affects the parasite actin cytoskeleton, resulting in an accumulation of actin signal that is independent of actin polymerization. This activity points to a target that modulates actin behavior in the cell either in terms of its regulation or its folding. More broadly, our data show that bacterial synthetic biosynthesis could become a suitable platform for antimalarial drug discovery, with potential applications in future high-throughput drug screening with otherwise chemically intractable natural products.

Correction: Single-molecule nanopore sensing of actin dynamics and drug binding.

[This corrects the article DOI: 10.1039/C9SC05710B.].