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Communication between tumors and the stroma of tumor-draining lymph nodes (TDLN) exists before metastasis arises, altering the structure and function of the TDLN niche. Transcriptional profiling of fibroblastic reticular cells (FRC), the dominant stromal population of lymph nodes, has revealed that FRCs in TDLNs are reprogrammed. However, the tumor-derived factors driving the changes in FRCs remain to be identified. Taking an unbiased approach, we have shown herein that lactic acid (LA), a metabolite released by cancer cells, was not only secreted by B16.F10 and 4T1 tumors in high amounts, but also that it was enriched in TDLNs. LA supported an upregulation of Podoplanin (Pdpn) and Thy1 and downregulation of IL7 in FRCs of TDLNs, making them akin to activated fibroblasts found at the primary tumor site. Furthermore, we found that tumor-derived LA altered mitochondrial function of FRCs in TDLNs. Thus, our results demonstrate a mechanism by which a tumor-derived metabolite connected with a low pH environment modulates the function of fibroblasts in TDLNs. How lymph node function is perturbed to support cancer metastases remains unclear. The authors show that tumor-derived LA drains to lymph nodes where it modulates the function of lymph node stromal cells, prior to metastatic colonization.

Supplementary Figure from Tumor-Derived Lactic Acid Modulates Activation and Metabolic Status of Draining Lymph Node Stroma

Communication between tumors and the stroma of tumor-draining lymph nodes (TDLN) exists before metastasis arises, altering the structure and function of the TDLN niche. Transcriptional profiling of fibroblastic reticular cells (FRC), the dominant stromal population of lymph nodes, has revealed that FRCs in TDLNs are reprogrammed. However, the tumor-derived factors driving the changes in FRCs remain to be identified. Taking an unbiased approach, we have shown herein that lactic acid (LA), a metabolite released by cancer cells, was not only secreted by B16.F10 and 4T1 tumors in high amounts, but also that it was enriched in TDLNs. LA supported an upregulation of Podoplanin (Pdpn) and Thy1 and downregulation of IL7 in FRCs of TDLNs, making them akin to activated fibroblasts found at the primary tumor site. Furthermore, we found that tumor-derived LA altered mitochondrial function of FRCs in TDLNs. Thus, our results demonstrate a mechanism by which a tumor-derived metabolite connected with a low pH environment modulates the function of fibroblasts in TDLNs. How lymph node function is perturbed to support cancer metastases remains unclear. The authors show that tumor-derived LA drains to lymph nodes where it modulates the function of lymph node stromal cells, prior to metastatic colonization.

Supplementary Figures S1-S7 and Tables S1 and S2

Skin cancer risk varies substantially across the body, yet how this relates to the mutations found in normal skin is unknown. Here we mapped mutant clones in skin from high- and low-risk sites. The density of mutations varied by location. The prevalence of NOTCH1 and FAT1 mutations in forearm, trunk, and leg skin was similar to that in keratinocyte cancers. Most mutations were caused by ultraviolet light, but mutational signature analysis suggested differences in DNA-repair processes between sites. Eleven mutant genes were under positive selection, with TP53 preferentially selected in the head and FAT1 in the leg. Fine-scale mapping revealed 10% of clones had copy-number alterations. Analysis of hair follicles showed mutations in the upper follicle resembled adjacent skin, but the lower follicle was sparsely mutated. Normal skin is a dense patchwork of mutant clones arising from competitive selection that varies by location.Significance:Mapping mutant clones across the body reveals normal skin is a dense patchwork of mutant cells. The variation in cancer risk between sites substantially exceeds that in mutant clone density. More generally, mutant genes cannot be assigned as cancer drivers until their prevalence in normal tissue is known.See related commentary by De Dominici and DeGregori, p. 227.This article is highlighted in the In This Issue feature, p. 211

The majority of biodiversity data is not findable, accessible, integratable, or reusable, partially because of a lack of metadata. Taxonomic names as metadata are useful, but not sufficient because these names may be updated as knowledge progresses. There is a great need for tools and services that can scale up to create and maintain metadata for the vast and varied long tail of dark data. Here we examine the use of GNFinder as a tool for creating and maintaining metadata using mentions of taxa in text from publications corresponding to data sets deposited in Dryad. Most studied taxa were mentioned in the publication using a properly formed scientific name, with a few exceptions for studies that only used vernacular names and only mentioned taxa in the corresponding files. GNFinder had a high F1 Score (0.86) representing a balance between precision (0.91) and recall (0.82). GNFinder had lower performance when a name string was an irregular abbreviation, had unexpected capitalization or punctuation, or contained a qualifier (like aff. or cf.). Approximately 14% of the name strings identified in text published from 1996 to 2012 were outdated and updated to a current, valid name. Automated metadata creation and maintenance at scale using GNFinder can make it easier to find biodiversity publications as demonstrated by the Biodiversity Heritage Library and HathiTrust.

Collection objects in natural science collections span a diverse set of object types of substantially different origin, physical composition, and relevance for different fields and methodologies of research and application. Object provenance is often characterized by elaborate series of interventions from collecting or observing originals in a natural state to generating derived objects that can be physically persistent or are suitable for a given use. This sequence of events gives rise to intermediate objects or object states that can be of a persistent or ephemeral nature in their own right. Detailed metadata on object provenance is vital to enable informed use of collection objects for research and other application areas. Providing the ability to generate, maintain, update and access such accounts is an important requirement for Collection Management Software (CMS). DINA (Digital Information System for Natural History Data, Glöckler et al. 2020)-compliant collection management software meets this challenge by using process- and state-based representation of object histories and modular application architecture as the main conceptual and architectural principles, respectively (Bölling et al. 2021). In applying these principles, we showcase how object provenance can be represented in the DINA system in cases where multiple objects, possibly of varying types, are derived from a single object, objects consist of parts of different biological individuals, object histories involve different types of objects such as living biological individuals, samples, and preserved specimens. multiple objects, possibly of varying types, are derived from a single object, objects consist of parts of different biological individuals, object histories involve different types of objects such as living biological individuals, samples, and preserved specimens. We highlight how the abstractions and categories used in the DINA model can be used to meet a variety of challenging use cases for representing collection object provenance. For instance, while the connections and relationships between living, preserved, and even destructively processed samples can be documented in DINA, these are ordinarily difficult to accommodate in a single information system.

The unravelling of the complexity of cellular metabolism is in its infancy. Cancer-associated genetic alterations may result in changes to cellular metabolism that aid in understanding phenotypic changes, reveal detectable metabolic signatures, or elucidate vulnerabilities to particular drugs. To understand cancer-associated metabolic transformation we performed untargeted metabolite analysis of 173 different cancer cell lines from 11 different tissues under constant conditions for 1099 different species using liquid chromatography-mass spectrometry (LC-MS). We correlate known cancer-associated mutations and gene expression programs with metabolic signatures, generating novel associations of known metabolic pathways with known cancer drivers. We show that metabolic activity correlates with drug sensitivity and use metabolic activity to predict drug response and synergy. Finally, we study the metabolic heterogeneity of cancer mutations across tissues, and find that genes exhibit a range of context specific, and more general metabolic control.

People are involved with the collection and curation of all biodiversity data, whether they are researchers, members of the public, taxonomists, conservationists, collection managers or wildlife managers. Knowing who those people are and connecting their biographical information to the biodiversity data they collect helps us contextualise their scientific work. We are particularly concerned with those people and communities involved in the collection and identification of biological specimens. People from herbaria and natural science museums have been collecting and preserving specimens from all over the world for more than 200 years. The problem is that many of these people are only known by unstandardized names written on specimen labels, often with only initials and without any biographical information. The process of identifying and linking individuals to their biographies enables us to improve the quality of the data held by collections while also quantifying the contributions of the often underappreciated people who collected and identified these specimens. This process improves our understanding of the history of collecting, and addresses current and future needs for maintaining the provenance of specimens so as to comply with national and international practices and regulations. In this talk we will outline the steps that collection managers, data scientists, curators, software engineers, and collectors can take to work towards fully disambiguated collections. With examples, we can show how they can use these data to help them in their work, in the evaluation of their collections, and in measuring the impact of individuals and organisations, local to global.

Cancer-causing missense mutations in the 3418 amino acid BRCA2 breast and ovarian cancer suppressor protein frequently affect a short (∼340 residue) segment in its carboxyl-terminal domain (DBD). Here, we identify a shared molecular mechanism underlying their pathogenicity. Pathogenic BRCA2 missense mutations cluster in the DBD’s helical domain (HD) and OB1-fold motifs, which engage the partner protein DSS1. Pathogenic - but not benign – DBD mutations weaken or abolish DSS1-BRCA2 assembly, provoking mutant BRCA2 oligomers that are excluded from the cell nucleus, and disable DNA repair by homologous DNA recombination (HDR). DSS1 inhibits the intracellular oligomerization of wildtype, but not mutant, forms of BRCA2. Remarkably, DSS1 expression corrects defective HDR in cells bearing pathogenic BRCA2 missense mutants with weakened, but not absent, DSS1 binding. Our findings identify a DSS1-mediated intracellular protein assembly mechanism that is disrupted by cancer-causing BRCA2 missense mutations, and suggest an approach for its therapeutic correction., Graphical Abstract Graphical AbstractCancer-causing mutations in the BRCA2 DBD impair DSS1 binding, provoking intracellular oligomerization and cytosolic mis-localization of the mutant BRCA2, and defective homologous recombination. These defects are reversed by DSS1 overexpression, for certain DBD mutants that retain small amounts of DSS1 binding.

Skin cancer risk varies substantially across the body, yet how this relates to the mutations found in normal skin is unknown. Here we mapped mutant clones in skin from high- and low-risk sites. The density of mutations varied by location. The prevalence of NOTCH1 and FAT1 mutations in forearm, trunk, and leg skin was similar to that in keratinocyte cancers. Most mutations were caused by ultraviolet light, but mutational signature analysis suggested differences in DNA-repair processes between sites. Eleven mutant genes were under positive selection, with TP53 preferentially selected in the head and FAT1 in the leg. Fine-scale mapping revealed 10% of clones had copy-number alterations. Analysis of hair follicles showed mutations in the upper follicle resembled adjacent skin, but the lower follicle was sparsely mutated. Normal skin is a dense patchwork of mutant clones arising from competitive selection that varies by location. Significance: Mapping mutant clones across the body reveals normal skin is a dense patchwork of mutant cells. The variation in cancer risk between sites substantially exceeds that in mutant clone density. More generally, mutant genes cannot be assigned as cancer drivers until their prevalence in normal tissue is known. See related commentary by De Dominici and DeGregori, p. 227. This article is highlighted in the In This Issue feature, p. 211

Wild-type gastrointestinal stromal tumours (wtGIST) are frequently caused by inherited pathogenic variants, or somatic alterations in the succinate dehydrogenase subunit genes (MGMT methylation analysis was performed on 65 tumour samples including 47 wtGIST (33 SDH-deficient wtGIST and 11 SDH preserved wtGIST) and 21 tyrosine kinase (TK) mutant GIST.MGMT promoter hypermethylation occurs exclusively in a subset of dSDH wtGIST. Data from this study support testing of tumour MGMT promoter methylation in patients with dSDH wtGIST to identify those patients who may benefit from most from TMZ therapy.

Biodiversity data is obtained by a variety of methodological approaches—including observation surveys, environmental sampling and biological object collection—employing diverse sample processing protocols and data transformations. While complete and accurate accounts of these data-generating processes are important to enable integration and informed reuse of data, the structure and content of published biodiversity data currently are often shaped by specific application goals. For example, data publishers that export specimen-based data from collection management systems for inclusion in aggregations like those in the Global Biodiversity Information Facility (GBIF) must frequently relax their internal models and produce unnatural joins to fit GBIF’s occurrences-based data structure. Third-party assertions over these aggregated data therefore assume the risk of irreproducibility or concept drift. Here we introduce process- and state-based representation of object histories as the main organizing principle for data about specimens and samples in Digital Information System for Natural History Data (DINA, Glöckler et al. 2020)-compliant collection management software (Fig. 1). Specimens, samples and objects in general are subjected to a variety of processes, including planned actions involving the object, e.g., collecting, preparing, subsampling, loaning. Object states are any particular mode of being of an object at a certain point in time. For example, any one intermediate step in preparing a collected specimen for long-term conservation in a collection would constitute an individual object state. An object’s history is the entire chain of these interrelated processes and states. We argue that using object histories as main conceptual modeling paradigm in DINA offers the generality required to accommodate a diverse, open set of use cases in biodiversity data representation, yet also offers the versatility to serve as basis for use-case specific data aggregation and presentation. Specifically, a representation based on object histories provides a coherent structure for documenting individual processes and states for any given object and for linking this documentation (e.g., textual descriptions or images pertaining to a given process or state), a natural representational structure of the real-world sequence of processes an object participates in and for the data generated in these processes (e.g., a DNA-extraction procedure and sequence information generated on its basis), a straightforward structure to link data about related objects (e.g., tissue samples, the biological specimen a bone is derived from) in a network of connected object histories. a coherent structure for documenting individual processes and states for any given object and for linking this documentation (e.g., textual descriptions or images pertaining to a given process or state), a natural representational structure of the real-world sequence of processes an object participates in and for the data generated in these processes (e.g., a DNA-extraction procedure and sequence information generated on its basis), a straightforward structure to link data about related objects (e.g., tissue samples, the biological specimen a bone is derived from) in a network of connected object histories. The approach is designed to be embedded in DINA’s modular application architecture, so that information on object histories can be accessed via corresponding APIs either through its own interfaces (Fig. 2) or by integration with external web services (Fig. 3). Viewing collection management tasks as part of object histories also informs delineation of modules to support these tasks with specialized functions and interfaces. It also admits the use of persistent, dereferencable identifiers for individual processes and states in object histories and for linking their representations to elements in ontologies and controlled vocabularies. In this contribution to the symposium, DINA's object histories as a main organizing principle for collection object data will be discussed and the utility of using it in the context of modular application architecture, data federation, and data integration in projects like BiCIKL will be illustrated.

The natural history specimens of the world have been documented on paper labels, often physically attached to the specimen itself. As we transcribe these data to make them digital and more useful for analysis, we make interpretations. Sometimes these interpretations are trivial, because the label is unambiguous, but often the meaning is not so clear, even if it is easily read. One key element that suffers from considerable ambiguity is people’s names. Though a person is indivisible, their name can change, is rarely unique and can be written in many ways. Yet knowing the people associated with data is incredibly useful. Data on people can be used to validate other data, simplify data capture, link together data across domains, reduce duplication-of-effort and facilitate data-gap-analysis. In addition, people data enable the discovery of individuals unique to our collections, the collective charting of the history of scientific researchers and the provision of credit to the people who deserve it (Groom et al. 2020). We foresee a future where the people associated with collections are not ambiguous, are shared globally, and data of all kinds are linked through the people who generate them. The TDWG People in Biodiversity Data Task Group is therefore working on a guide to the disambiguation of people in natural history collections. The ultimate goal is to connect the various strings of characters on specimen labels and other documentation to persistent identifiers (PIDs) that unambiguously link a name “string” to the identity of a person. In working towards this goal, 150 volunteers in the Bionomia project have linked 21 million specimens to persistent identifiers for their collectors and determiners. An additional 2 million specimens with links to identifiers for people have already emerged directly from collections that make use of the recently ratified Darwin Core terms recordedByID and identifiedByID. Furthermore, the CETAF Botany Pilot conducted among a group of European herbaria and museums has connected over 1.4 million specimens to disambiguated collectors (Güntsch et al. 2021). Still, given the estimated 2 billion (Ariño 2010) natural history specimens globally, there is much more disambiguation to be done. The process of disambiguation starts with a trigger, which is often the transcription of a specimen’s label data. Unambiguous identification of the collector may facilitate this transcription, as it offers knowledge of their biographical details and collecting habits, allowing us to infer missing information such as collecting date or locality. Another trigger might be the flagging of inconsistent data during data entry or resulting from data quality processes, revealing for instance that multiple collectors have been conflated. A disambiguation trigger is followed by the gathering of data, then the evaluation of the results and finally by the documentation of the new information. Disambiguation is not always straightforward and there are many pitfalls. It requires access to biographical data, and identifiers to be minted. In the case of living people, they have to cooperate with being disambiguated and we have to follow legal and ethical guidelines. In the case of dead people, particularly those long dead, disambiguation may require considerable research. We will present the progress made by the People in Biodiversity Data Task Group and their recommendations for disambiguation in collections. We want to encourage other institutions to engage with a global effort of linking people to persistent identifiers to collaboratively improve all collection data.

AimsWild-type gastrointestinal stromal tumours (wtGIST) are frequently caused by inherited pathogenic variants, or somatic alterations in the succinate dehydrogenase subunit genes (SDHx). Succinate dehydrogenase is a key enzyme in the citric acid cycle. SDH deficiency caused bySDHxinactivation leads to an accumulation of succinate, which inhibits DNA and histone demethylase enzymes, resulting in global hypermethylation. Epigenetic silencing of the DNA repair gene MGMT has proven utility as a positive predictor of the therapeutic efficacy of the alklyating drug temozolomide (TMZ) in tumours such as glioblastoma multiforme. The aim of this study was to examine MGMT promoter methylation status in a large cohort of GIST.MethodsMGMT methylation analysis was performed on 65 tumour samples including 47 wtGIST (33 SDH-deficient wtGIST and 11 SDH preserved wtGIST) and 21 tyrosine kinase (TK) mutant GIST.ResultsMGMTpromoter methylation was detected in 8 cases of SDH-deficient (dSDH) GIST but in none of the 14 SDH preserved wild-type GIST or 21 TK mutant GIST samples analysed. Mean MGMT methylation was significantly higher (p 0.0449) and MGMT expression significantly lower (pSDHxsubunit gene mutations or SDHC epimutation status and mean MGMT methylation levels.ConclusionMGMT promoter hypermethylation occurs exclusively in a subset of dSDH wtGIST. Data from this study support testing of tumour MGMT promoter methylation in patients with dSDH wtGIST to identify those patients who may benefit from most from TMZ therapy.

Blood malignancies arise from the dysregulation of haematopoiesis. The type of blood cell and the specific order of oncogenic events initiating abnormal growth ultimately determine the cancer subtype and subsequent clinical outcome. HOXA9 plays an important role in acute myeloid leukaemia (AML) prognosis by promoting blood cell expansion and altering differentiation; however, the function of HOXA9 in other blood malignancies is still unclear. Here, we demonstrate the importance of this gene in chronic myeloproliferative neoplasms (MPN) and highlight the biological switch and prognosis marker properties of HOXA9 in AML and MPN. This binary switch function can explain the clinical stratification of these two blood disorders. First, we establish the ability of HOXA9 to stratify AML patients with distinct cellular and clinical outcomes. Then, through the use of a computational network model of MPN, we show that the self-activation of HOXA9 and its relationship to JAK2 and TET2 can explain the branching progression of JAK2/TET2 mutant MPN patients towards divergent clinical characteristics. Finally, we predict a connection between the RUNX1 and MYB genes and a suppressive role for the NOTCH pathway in MPN diseases.

People are one of the best known and most stable entities in the biodiversity knowledge graph. The wealth of public information associated with people and the ability to identify them uniquely open up the possibility to make more use of these data in biodiversity science. Person data are almost always associated with entities such as specimens, molecular sequences, taxonomic names, observations, images, traits and publications. For example, the digitization and the aggregation of specimen data from museums and herbaria allow us to view a scientist’s specimen collecting in conjunction with the whole corpus of their works. However, the metadata of these entities are also useful in validating data, integrating data across collections and institutional databases and can be the basis of future research into biodiversity and science. In addition, the ability to reliably credit collectors for their work has the potential to change the incentive structure to promote improved curation and maintenance of natural history collections.

The recent development of highly sensitive DNA sequencing techniques has detected large numbers of missense mutations of genes, including NOTCH1 and 2, in ageing normal tissues. Driver mutations persist and propagate in the tissue through a selective advantage over both wild-type cells and alternative mutations. This process of selection can be considered as a large scale, in vivo screen for mutations that increase clone fitness. It follows that the specific missense mutations that are observed in individual genes may offer us insights into the structure-function relationships. Here we show that the positively selected missense mutations in NOTCH1 and NOTCH2 in human oesophageal epithelium cause inactivation predominantly through protein misfolding. Once these mutations are excluded, we further find statistically significant evidence for selection at the ligand binding interface and calcium binding sites. In this, we observe stronger evidence of selection at the ligand interface on EGF12 over EGF11, suggesting that in this tissue EGF12 may play a more important role in ligand interaction. Finally, we show how a mutation hotspot in the NOTCH1 transmembrane helix arises through the intersection of both a high mutation rate and residue conservation. Together these insights offer a route to understanding the mechanism of protein function through in vivo mutant selection.

Voltage sensitive potassium channels play an important role in controlling membrane potential and ionic homeostasis in the gut and have been implicated in gastrointestinal (GI) cancers. Through large scale analysis of 1594 patients with GI cancers coupled with in vitro models we find KCNQ family genes are mutated in ~30% of patients, and play therapeutically targetable roles in GI cancer growth. KCNQ1 and KCNQ3 mediate the WNT pathway and MYC to increase proliferation, and its resultant effects on cadherins junctions. This also highlights novel roles for KCNQ3 in non-excitable tissues. We additionally discover that activity of KCNQ3 sensitises cancer cells to existing potassium channel inhibitors, and that inhibition of KCNQ activity reduces proliferation of GI cancer. These findings reveal a novel and exploitable role for potassium channels in the advancement of human cancer, and highlight that supplemental treatments for GI cancers may exist through KCNQ inhibitors.SIGNIFICANCEKCNQ channels modulate the WNT pathway and MYC signalling, and drive growth of gastrointestinal cancers. Available drugs modulate these pathways and offer therapeutic potential in gastrointestinal cancer.

In an age where the volume of data regarding biological systems exceeds our ability to analyse it, many researchers are looking towards systems biology and computational modelling to help unravel the complexities of gene and protein regulatory networks. In particular, the use of discrete modelling allows generation of signalling networks in the absence of full quantitative descriptions of systems, which are necessary for ordinary differential equation (ODE) models. In order to make such techniques more accessible to mainstream researchers, tools such as the BioModelAnalyzer (BMA) have been developed to provide a user-friendly graphical interface for discrete modelling of biological systems. Here we use the BMA to build a library of discrete target functions of known canonical molecular interactions, translated from ordinary differential equations (ODEs). We then show that these BMA target functions can be used to reconstruct complex networks, which can correctly predict many known genetic perturbations. This new library supports the accessibility ethos behind the creation of BMA, providing a toolbox for the construction of complex cell signalling models without the need for extensive experience in computer programming or mathematical modelling, and allows for construction and simulation of complex biological systems with only small amounts of quantitative data.

Bionomia, https://bionomia.net previously called Bloodhound Tracker, was launched in August 2018 with the aim of illustrating the breadth and depth of expertise required to collect and identify natural history specimens represented in the Global Biodiversity Information Facility (GBIF). This required that specimens and people be uniquely identified and that a granular expression of actions (e.g. "collected", "identified") be adopted. The Darwin Core standard presently combines agents and their actions into the conflated terms recordedBy and identifiedBy whose values are typically unresolved and unlinked text strings. Bionomia consists of tools, web services, and a responsive website, which are all used to efficiently guide users to resolve and unequivocally link people to specimens via first-class actions collected or identified. It also shields users from the complexity of casting together and seamlessly integrating the services of four giant initiatives: ORCID, Wikidata, GBIF, and Zenodo. All of these initiatives are financially sustainable and well-used by many stakeholders, well-outside this narrow user-case. As a result, the links between person and specimen made by users of Bionomia are given every opportunity to persist, to represent credit for effort, and to flow into collection management systems as meaningful new entries. To date, 13M links between people and specimens have been made including 2M negative associations on 12.5M specimen records. These links were either made by the collectors themselves or by 84 people who have attributed specimen records to their peers, mentors and others they revere. Integration With ORCID and Wikidata People are identified in Bionomia through synchronization with ORCID and Wikidata by reusing their unique identifiers and drawing in their metadata. ORCID identifiers are used by living researchers to link their identites to their research outputs. ORCID services include OAuth2 pass-through authentication for use by developers and web services for programmatic access to its store of public profiles. These contain elements of metadata such as full name, aliases, keywords, countries, education, employment history, affiliations, and links to publications. Bionomia seeds its search directory of people by periodically querying ORCID for specific user-assigned keywords as well as directly though account creation via OAuth2 authentication. Deceased people are uniquely identified in Bionomia through integration with Wikidata by caching unique 'Q' numbers (identifiers), full names and aliases, countries, occupations, as well as birth and death dates. Profiles are seeded from Wikidata through daily queries for properties that are likely to be assigned to collectors of natural history specimens such as "Entomologists of the World ID" (= P5370) or "Harvard Index of Botanists ID" (= P6264). Because Wikidata items may be merged, Bionomia captures these merge events, re-associates previously made links to specimen records, and mirrors Wikidata's redirect behaviour. A Wikidata property called "Bionomia ID" (= P6944), whose values are either ORCID identifiers or Wikidata 'Q' numbers, helps facilitate additional integration and reuse. Integration with GBIF Specimen data are downloaded wholesale as Darwin Core Archives from GBIF every two weeks. The purpose of this schedule is to maintain a reasonable synchrony with source data that balances computation time with the expections of users who desire the most up-to-date view of their specimen records. Collectors with ORCID accounts who have elected to receive notice, are informed via email message when the authors of newly published papers have made use of their specimen records downloaded from GBIF. Integration with Zenodo Finally, users of Bionomia may integrate their ORCID OAuth2 authentication with Zenodo, an industry-recognized archive for research data, which enjoys support from the Conseil Européen pour la Recherche Nucléaire (CERN). At the user's request, their specimen data represented as CSV (comma-separated values) and JSON-LD (JavaScript Object Notation for Linked Data) documents are pushed into Zenodo, a DataCite DOI is assigned, and a formatted citation appears on their Bionomia profile. New versions of these files are pushed to Zenodo on the user's behalf when new specimen records are linked to them. If users have configured their ORCID account to listen for new entries in DataCite, a new work entry will also be made in their ORCID profile, thus sealing a perpetual, semi-automated loop betwen GBIF and ORCID that tidily showcases their efforts at collecting and identifying natural history specimens. Technologies Used Bionomia uses Apache Spark via scripts written in Scala, a human name parser written in Ruby called dwc_agent, queues of jobs executed through Sidekiq, scores of pairwise similarities in the structure of human names stored in Neo4j, data persistence in MySQL, and a search layer in Elasticsearch. Here, I expand on lessons learned in the construction and maintenance of Bionomia, emphasize the criticality of recognizing the early efforts made by a fledgling community of enthusiasts, and describe useful tools and services that may be integrated into collection management systems to help churn strings of unresolved, unlinked collector and determiner names into actionable identifiers that are gateways to rich sources of information.

A discussion session held at a National Science Foundation-sponsored Herbarium Networks Workshop at Michigan State University in September of 2004 resulted in a rallying objective: make all botanical specimen information in United States collections available online by 2020. Rabeler and Macklin 2006 outlined a toolkit for realizing this ambitious goal, which included: a review of relevant and state-of-the-art web resources, data exchange standards and, mechanisms to maximize efficiencies while minimizing costs. a review of relevant and state-of-the-art web resources, data exchange standards and, mechanisms to maximize efficiencies while minimizing costs. Given that we are now in the year 2020, it seems appropriate to examine the progress towards the objective of making all US botanical specimen collections data available online. Our presentation will attempt to answer several questions: How close have we come to meeting the original objective? What fraction of “digitized” specimens are minimally represented by a catalog number, a determination, and/or a photograph? What fraction has been thoroughly transcribed? How close have we come to attaining a seamlessly integrated, comprehensive, and national view of botanical specimen data that guides a stakeholder to appropriate resources regardless of their entry point? What “holes” in this effort still exist and what might be required to fill them? How close have we come to meeting the original objective? What fraction of “digitized” specimens are minimally represented by a catalog number, a determination, and/or a photograph? What fraction has been thoroughly transcribed? How close have we come to attaining a seamlessly integrated, comprehensive, and national view of botanical specimen data that guides a stakeholder to appropriate resources regardless of their entry point? What “holes” in this effort still exist and what might be required to fill them? Given our interest in the success of both the Global Biodiversity Information Facility (GBIF) and the Integrated Digitized Biocollections (iDigBio), as well as the overwhelming likelihood that either one of these initiatives is the usual entry point for someone seeking US-based botanical data, we approached the answers to the above questions by first crafting a repeatable data download and processing workflow in early July 2020. This resulted in 25.6M records of plant, fungi, and Chromista from 216 datasets available through GBIF and 32.8M comparable records available through iDigBio from 525 recordsets. We attempted to align these seemingly discordant sets of records and also chose Darwin Core terms that were best suited to match the four hierarchical levels of digitization defined in the Minimal Information for Digital Specimens (MIDS) (van Egmond et al. 2019). During the analysis/comparison of the datasets, we found several examples where the number of data records from an institution seemed much lower than expected. From a combination of analyzing record content in GBIF/iDigBio and consulting regional/taxonomic portals, it became evident that, besides datasets only being included in either GBIF or iDigBio, there was a significant number of records in regional/taxonomic portals that were not yet made available through either GBIF or iDigBio. Progress on digitization has benefited greatly from the US National Science Foundation's creation of the Advancing Digitization of Biodiversity Collections (ADBC) program, and funding of the 15 Thematic Collection Networks (TCN). The launching of new projects and the ensuing digitization of herbarium collections have led to a multitude of new specimen portals and the enhancement of existing software like Symbiota (Gries et al. 2014). But, it has also led to insufficient data sharing among projects and inadequately aligned data synchronization practices between aggregators. Consistency in terms of data availability and quality between GBIF and iDigBio is low, and the chronic lack of record-level identifiers consistently restricts the flow of enhancements made to records. We conclude that there remains substantial work to be done on the national infrastructure and on international best practices to help facilitate collaboration and to realize the original objective of making all US botanical specimen collections data available online.

Genomic evidence suggests that the causative virus of COVID-19 (SARS-CoV-2) was introduced to humans from horseshoe bats (family Rhinolophidae) (Andersen et al. 2020) and that species in this family as well as in the closely related Hipposideridae and Rhinonycteridae families are reservoirs of several SARS-like coronaviruses (Gouilh et al. 2011). Specimens collected over the past 400 years and curated by natural history collections around the world provide an essential reference as we work to understand the distributions, life histories, and evolutionary relationships of these bats and their viruses. While the importance of biodiversity specimens to emerging infectious disease research is clear, empowering disease researchers with specimen data is a relatively new goal for the collections community (DiEuliis et al. 2016). Recognizing this, a team from Florida State University is collaborating with partners at GEOLocate, Bionomia, University of Florida, the American Museum of Natural History, and Arizona State University to produce a deduplicated, georeferenced, vetted, and versioned data product of the world's specimens of horseshoe bats and relatives for researchers studying COVID-19. The project will serve as a model for future rapid data product deployments about biodiversity specimens. The project underscores the value of biodiversity data aggregators iDigBio and the Global Biodiversity Information Facility (GBIF), which are sources for 58,617 and 79,862 records, respectively, as of July 2020, of horseshoe bat and relative specimens held by over one hundred natural history collections. Although much of the specimen-based biodiversity data served by iDigBio and GBIF is high quality, it can be considered raw data and therefore often requires additional wrangling, standardizing, and enhancement to be fit for specific applications. The project will create efficiencies for the coronavirus research community by producing an enhanced, research-ready data product, which will be versioned and published through Zenodo, an open-access repository (see doi.org/10.5281/zenodo.3974999). In this talk, we highlight lessons learned from the initial phases of the project, including deduplicating specimen records, standardizing country information, and enhancing taxonomic information. We also report on our progress to date, related to enhancing information about agents (e.g., collectors or determiners) associated with these specimens, and to georeferencing specimen localities. We seek also to explore how much we can use the added agent information (i.e., ORCID iDs and Wikidata Q identifiers) to inform our georeferencing efforts and to support crediting those collecting and doing identifications. The project will georeference approximately one third of our specimen records, based on those lacking geospatial coordinates but containing textual locality descriptions. We furthermore provide an overview of our holistic approach to enhancing specimen records, which we hope will maximize the value of the bat specimens at the center of what has been recently termed the "extended specimen network" (Lendemer et al. 2020). The centrality of the physical specimen in the network reinforces the importance of archived materials for reproducible research. Recognizing this, we view the collections providing data to iDigBio and GBIF as essential partners, as we expect that they will be responsible for the long-term management of enhanced data associated with the physical specimens they curate. We hope that this project can provide a model for better facilitating the reintegration of enhanced data back into local specimen data management systems.

The DINA Consortium (DINA = “DIgital information system for NAtural history data”, https://dina-project.net) is a framework for like-minded practitioners of natural history collections to collaborate on the development of distributed, open source software that empowers and sustains collections management. Target collections include zoology, botany, mycology, geology, paleontology, and living collections. The DINA software will also permit the compilation of biodiversity inventories and will robustly support both observation and molecular data. The DINA Consortium focuses on an open source software philosophy and on community-driven open development. Contributors share their development resources and expertise for the benefit of all participants. The DINA System is explicitly designed as a loosely coupled set of web-enabled modules. At its core, this modular ecosystem includes strict guidelines for the structure of Web application programming interfaces (APIs), which guarantees the interoperability of all components (https://github.com/DINA-Web). Important to the DINA philosophy is that users (e.g., collection managers, curators) be actively engaged in an agile development process. This ensures that the product is pleasing for everyday use, includes efficient yet flexible workflows, and implements best practices in specimen data capture and management. There are three options for developing a DINA module: create a new module compliant with the specifications (Fig. 1), modify an existing code-base to attain compliance (Fig. 2), or wrap a compliant API around existing code that cannot be or may not be modified (e.g., infeasible, dependencies on other systems, closed code) (Fig. 3). create a new module compliant with the specifications (Fig. 1), modify an existing code-base to attain compliance (Fig. 2), or wrap a compliant API around existing code that cannot be or may not be modified (e.g., infeasible, dependencies on other systems, closed code) (Fig. 3). All three of these scenarios have been applied in the modules recently developed: a module for molecular data (SeqDB), modules for multimedia, documents and agents data and a service module for printing labels and reports: The SeqDB collection management and molecular tracking system (Bilkhu et al. 2017) has evolved through two of these scenarios. Originally, the required architectural changes were going to be added into the codebase, but after some time, the development team recognised that the technical debt inherent in the project wasn’t worth the effort of modification and refactoring. Instead a new codebase was created bringing forward the best parts of the system oriented around the molecular data model for Sanger Sequencing and Next Generation Sequencing (NGS) workflows. In the case of the Multimedia and Document Store module and the Agents module, a brand new codebase was established whose technology choices were aligned with the DINA vision. These two modules have been created from fundamental use cases for collection management and digitization workflows and will continue to evolve as more modules come online and broaden their scope. The DINA Labels & Reporting module is a generic service for transforming data in arbitrary printable layouts based on customizable templates. In order to use the module in combination with data managed in collection management software Specify (http://specifysoftware.org) for printing labels of collection objects, we wrapped the Specify 7 API with a DINA-compliant API layer called the “DINA Specify Broker”. This allows for using the easy-to-use web-based template engine within the DINA Labels & Reports module without changing Specify’s codebase. In our presentation we will explain the DINA development philosophy and will outline benefits for different stakeholders who directly or indirectly use collections data and related research data in their daily workflows. We will also highlight opportunities for joining the DINA Consortium and how to best engage with members of DINA who share their expertise in natural science, biodiversity informatics and geoinformatics.

Fumarate Hydratase (FH) is an enzyme of the citric acid (TCA) cycle that is responsible for reversibly catalysing the conversion between fumarate and malate. FH loss and subsequent buildup of the oncometabolite fumarate causes hereditary leiomyomatosis and renal cell carcinoma. We explore the mutational landscape of FH in silico, predict the functional effects of many already detected mutations, and categorise detected but un-characterised mutations in human populations. Using mutational energy predicting tools such as Rosetta and FoldX we accurately predict mutations and mutational hotspots with high disruptive capability. Furthermore, through performing molecular dynamics simulations we show that hinge regions of the protein can be stabilized or destabilized by mutations, with new mechanistic implications of the consequences on the binding affinity of the enzyme for its substrates. Finally, we categorise all potential mutations in FH into functional groups, and predict which known mutations in the human population are loss-of-function, and therefore predispose patients to papillary renal carcinoma – we validate our findings through analysis of metabolomics data of characterized cell lines.

For the last 15 years, Biodiversity Information Standards (TDWG) has recognized two competing standards for organism occurrence data, ABCD (Access to Biological Collections Data; Holetschek et al. 2012) and DarwinCore (Wieczorek et al. 2012). These two representations emerged from contrasting strategies for mobilizing information about organism occurrences (also commonly called species occurrence data). ABCD was capable of representing details of more kinds of information, but was necessarily more complicated. DarwinCore, on the other hand, was simpler but more limited in its ability to represent data of different kinds and formats. TDWG endorsed both standards because the different projects and communities that generated them remained dedicated to their different strategies and tool sets, and the Global Biodiversity Information Facility (GBIF) developed the ability to integrate data published in either standard. Since their inceptions, DarwinCore and ABCD have become more similar. DarwinCore has gotten more complicated through the addition of terms and has begun to assign terms to classes. ABCD is now expressed in RDF (Resource Description Framework), potentially enabling re-use of terms with alternative structures among classes. At the same time, methodologies for conceptual modeling and representing complex scientific data have continued to evolve. In particular, a suite of modeling and data representation methods related to linked data and the semantic web, i.e., RDF, SKOS (Simple Knowledge Organization System), and OWL (web Ontology Language), promise to make it easier for us to reconcile shared concepts among different representations or schemas. A mapping between ABCD 2.1 and DarwinCore has existed since before 2005.*1 ABCD 3.0 and DarwinCore are both now represented in RDF. In addition, the BioCollections Ontology (BCO) covers many of the shared concepts and is derived from the Basic Formal Ontology (BFO), an upper level ontology that has oriented many other biomedical ontologies. Reconciling ABCD and DarwinCore through alignment with BCO (in the OBO Foundry; Smith et al. 2007) would better connect TDWG standards to other domains in biology. We appreciate that many working scientists and data managers perceive ontologies as overly complicated. To mitigate the steep learning curve associated with ontologies, we expect to create simpler application profiles or schemas to guide and serve narrower communities of practice within the wider biodiversity domain. We also plan to integrate the current work of the Taxonomic Names and Concepts Interest Group and thereby eliminate the redundancy between DarwinCore and Taxonomic Concepts Transfer Schema (TCS; Kennedy et al. 2006). At the time of this writing, we have only agreements from the authors (i.e., conveners of relevant TDWG Interest Groups and other key stakeholders) to collaborate in pursuit of these common goals. In this presentation we will give a more detailed description of our objectives and products, the methods we are using to achieve them, and our progress to date.

A vast amount of biodiversity data is reported in the primary taxonomic literature. In the past, we have demonstrated the use of semantic enhancement to extract data from taxonomic literature and make it available to a network of databases (Miller et al. 2015). For technical reasons, semantic enhancement of taxonomic literature is most efficient when customized according to the format of a particular journal. This journal-based approach captures and disseminates data on whatever taxa happen to be published therein. But if we want to extract all treatments on a particular taxon of interest, these are likely to be spread across multiple journals. Fortunately, the GoldenGATE Imagine document editor (Sautter 2019) is flexible enough to parse most taxonomic literature. Tyrannosaurus rex is an iconic dinosaur with broad public appeal, as well as the subject of more than a century of scholarship. The Naturalis Biodiversity Center recently acquired a specimen that has become a major attraction in the public exhibit space. For most species on earth, the primary taxonomic literature contains nearly everything that is known about it. Every described species on earth is the subject of one or more taxonomic treatments. A taxon-based approach to semantic enhancement can mobilize all this knowledge using the network of databases and resources that comprise the modern biodiversity informatics infrastructure. When a particular species is of special interest, a taxon-based approach to semantic enhancement can be a powerful tool for scholarship and communication. In light of this, we resolved to semantically enhance all taxonomic treatments on T. rex. Our objective was to make these treatments and associated data available for the broad range of stakeholders who might have an interest in this animal, including professional paleontologists, the curious public, and museum exhibits and public communications personnel. Among the routine parsing and data sharing activities in the Plazi workflow (Agosti and Egloff 2009), taxonomic treatments, as well as cited figures, are deposited in the Biodiversity Literature Repository (BLR), and occurrence records are shared with the Global Biodiversity Information Facility (GBIF). Treatment citations were enhanced with hyperlinks to the cited treatment on TreatmentBank, and specimen citations were linked to their entries on public facing collections databases. We used the OpenBiodiv biodiversity knowledge graph (Senderov et al. 2017) to discover other taxa mentioned together with T. rex, and to create a timeline of T. rex research to evaluate the impact of individual researchers and specimen repositories to T. rex research. We contributed treatment links to WikiData, and queried WikiData to discover identifiers to different platforms holding data about T. rex. We used bloodhound-tracker.net to disambiguate human agents, like collectors, identifiers, and authors. We evaluate the adequacy of the fields currently available to extract data from taxonomic treatments, and make recommendations for future standards.

Communication between tumors and the stroma of tumor draining lymph nodes (TDLNs) exists before metastasis arises, altering structure and function of the TDLN niche. Transcriptional profiling of fibroblastic reticular cells (FRCs), the dominant stromal population of the LN, revealed reprogramming of these cells in immune related pathways, but also in fibroblast activation and mitochondrial function. However, tumor derived factors driving the changes in FRCs remained to be identified. Taking an unbiased approach, we show that lactate, a metabolite released by cancer cells, elicits upregulation of Pdpn and Thy1 in FRCs of TDLNs, making them akin to activated fibroblasts found at the primary tumor site. Furthermore, we show that tumor-derived lactate alters mitochondrial function of FRCs of TDLNs. Thus, our results demonstrate a novel mechanism by which a tumor-derived metabolite modulates the function of fibroblasts in TDLNs.

Osmotic regulation is a vital homoeostatic process in all cells and tissues. Cells initially respond to osmotic stresses by activating transmembrane transport proteins to move osmotically active ions. Disruption of ion and water transport is frequently observed in cellular transformations such as cancer. We report that genes involved in membrane transport are significantly deregulated in many cancers, and that their expression can distinguish cancer cells from normal cells with a high degree of accuracy. We present an executable model of osmotic regulation and membrane transport in mammalian cells, providing a mechanistic explanation for phenotype change in varied disease states, and accurately predicting behaviour from single cell expression data. We also predict key proteins involved in cellular transformation, SLC4A3 (AE3), and SLC9A1 (NHE1). Furthermore, we predict and verify a synergistic drug combination in vitro, of sodium and chloride channel inhibitors, which target the osmoregulatory network to reduce cancer-associated phenotypes in fibroblasts., Aberrant ion transporter expression disrupts osmoregulation in many cancers. Here, the authors introduce an executable model of osmotic regulation and membrane transport, illuminating the mechanistic basis of multiple cellular cancer phenotypes and suggesting therapeutic avenues.

Glycolipids are key components of mammalian cell membranes, influencing a diverse range of cellular functions. For example, a number of receptor tyrosine kinases, including the epidermal growth factor receptor (EGFR), are allosterically regulated by the glycolipid monosialodihexosylganglioside (GM3). Recent advances in molecular dynamics methods, especially the development of coarse-grained models, have enabled simulations of increasingly complex models of cell membranes. We demonstrate these methodological developments via a case study of a coarse-grained model for the ganglioside GM3. This glycolipid is included in simulations of a mixed lipid bilayer model reflecting the compositional complexity of a mammalian cell membrane. The resultant membrane model is used to simulate the interactions of GM3 with the transmembrane domain of the EGFR., Highlights • We review recent progress in molecular dynamics simulations of glycolipids. • A coarse-grained model of the ganglioside GM3 is described. • The GM3 model is used in coarse-grained simulations of a mammalian cell membrane. • We describe the interactions of GM3 with the transmembrane domain of the EGFR.

In an age where the volume of data regarding biological systems exceeds our ability to analyse it, many researchers are looking towards systems biology and computational modelling to help unravel the complexities of gene and protein regulatory networks. In particular, the use of discrete modelling allows generation of signalling networks in the absence of full quantitative descriptions of systems, which are necessary for ordinary differential equation (ODE) models. In order to make such techniques more accessible to mainstream researchers, tools such as the BioModelAnalyzer (BMA) have been developed to provide a user-friendly graphical interface for discrete modelling of biological systems. Here we use the BMA to build a library of discrete target functions of known canonical molecular interactions, translated from ordinary differential equations (ODEs). We then show that these BMA target functions can be used to reconstruct complex networks, which can correctly predict many known genetic perturbations. This new library supports the accessibility ethos behind the creation of BMA, providing a toolbox for the construction of complex cell signalling models without the need for extensive experience in computer programming or mathematical modelling, and allows for construction and simulation of complex biological systems with only small amounts of quantitative data.AUTHOR SUMMARYOrdinary differential equation (ODE) based models are a popular approach for modelling biological networks. A limitation of ODE models is that they require complete networks and detailed kinetic parameterisation. An alternative is the use of discrete, executable models, in which nodes are assigned discrete value ranges, and the relationship between them defined with simple mathematical operations. One tool for constructing such models is the BioModelAnalyzer (BMA), an open source and publicly available (https://www.biomodelanalyzer.org) software, aimed to be fully usable by researchers without extensive computational or mathematical experience. A fundamental question for executable models is whether the high level of abstraction substantially reduces expressivity relative to continuous approaches. Here, we present a canonical library of biological signalling motifs, initially defined by Tyson et al (2003), translated for the first time into the BMA. We show that; 1) these motifs are easily and fully translatable from continuous to discrete models, 2) Combining these motifs in a computationally naïve way generates a fully functional and predictive model of the yeast cell cycle.

Lung adenocarcinoma accounts for ∼40% of lung cancers, the leading cause of cancer-related death worldwide, and current therapies provide only limited survival benefit. Approximately half of lung adenocarcinomas harbor mutations in TP53 (p53), making these mutants appealing targets for lung cancer therapy. As mutant p53 remains untargetable, mutant p53-dependent phenotypes represent alternative targeting opportunities, but the prevalence and therapeutic relevance of such effects (gain of function and dominant-negative activity) in lung adenocarcinoma are unclear. Through transcriptional and functional analysis of murine KrasG12D-p53null, -p53R172H (conformational), and -p53R270H (contact) mutant lung tumors, we identified genotype-independent and genotype-dependent therapeutic sensitivities. Unexpectedly, we found that wild-type p53 exerts a dominant tumor-suppressive effect on mutant tumors, as all genotypes were similarly sensitive to its restoration in vivo. These data show that the potential of p53 targeted therapies is comparable across all p53-deficient genotypes and may explain the high incidence of p53 loss of heterozygosity in mutant tumors. In contrast, mutant p53 gain of function and their associated vulnerabilities can vary according to mutation type. Notably, we identified a p53R270H-specific sensitivity to simvastatin in lung tumors, and the transcriptional signature that underlies this sensitivity was also present in human lung tumors, indicating that this therapeutic approach may be clinically relevant.

Background: Recent years have seen a surge in projects that produce large volumes of structured, machine-readable biodiversity data. To make these data amenable to processing by generic, open source "data enrichment" workflows, they are increasingly being represented in a variety of standards-compliant interchange formats. Here, we report on an initiative in which software developers and taxonomists came together to address the challenges and highlight the opportunities in the enrichment of such biodiversity data by engaging in intensive, collaborative software development: The Biodiversity Data Enrichment Hackathon. Results: The hackathon brought together 37 participants (including developers and taxonomists, i.e. scientific professionals that gather, identify, name and classify species) from 10 countries: Belgium, Bulgaria, Canada, Finland, Germany, Italy, the Netherlands, New Zealand, the UK, and the US. The participants brought expertise in processing structured data, text mining, development of ontologies, digital identification keys, geographic information systems, niche modeling, natural language processing, provenance annotation, semantic integration, taxonomic name resolution, web service interfaces, workflow tools and visualisation. Most use cases and exemplar data were provided by taxonomists. One goal of the meeting was to facilitate re-use and enhancement of biodiversity knowledge by a broad range of stakeholders, such as taxonomists, systematists, ecologists, niche modelers, informaticians and ontologists. The suggested use cases resulted in nine breakout groups addressing three main themes: i) mobilising heritage biodiversity knowledge; ii) formalising and linking concepts; and iii) addressing interoperability between service platforms. Another goal was to further foster a community of experts in biodiversity informatics and to build human links between research projects and institutions, in response to recent calls to further such integration in this research domain. Conclusions: Beyond deriving prototype solutions for each use case, areas of inadequacy were discussed and are being pursued further. It was striking how many possible applications for biodiversity data there were and how quickly solutions could be put together when the normal constraints to collaboration were broken down for a week. Conversely, mobilising biodiversity knowledge from their silos in heritage literature and natural history collections will continue to require formalisation of the concepts (and the links between them) that define the research domain, as well as increased interoperability between the software platforms that operate on these concepts.

Research collections are an important tool for understanding the Earth, its systems, and human interaction. Despite the importance of collections, many are not maintained or curated as thoroughly as we would like. Part of the reason for this is the lack of professional reward for collection, curation, or maintenance. To address this gap in attribution metadata, the Research Data Alliance (RDA) and the Biodiversity Information Standards (TDWG) organization co-endorsed a Working Group to create recommendations for the representation of attribution metadata. After 18 months, this Working Group recommended the use of PROV entities and properties to link people (Agent), the curatorial actions they perform (Activity), and the digital or physical objects they are curating (Entity). Assigning a Role to an Agent is optional. These recommendations are discussed in the context of the RDA, TDWG, and existing standards. Future work includes adapting these recommendations to the specific needs of TDWG and developing a pilot application in collaboration with ORCID and the Data Futures project.

Biological information, both new and old, is increasingly available in thousands of on-line sites. Biological information relates to elements as small as subatomic particles, and as large as the entire biosphere, and to processes that last from less than a femtosecond to many billions of years. Our economy, supply of food and materials, our health, and individual and collective well-being are set within the context of our natural world. Our world is under pressure from the demands of a growing population. Biologists need new ways to access, organize and analyze biological information to make new styles of research possible to better predict the nature of future change and to inform decisions makers. TDWG has promoted standardization that facilitates communication, but there is no overall architecture that interconnects the digital resources to better serve a wider community. The research funding paradigm leads to imaginative but competitive and short-lived enterprises. The Unifying Biology Through Informatics (UBTI) programme will explore the challenges that have to be overcome to add a cyberinfrastructure agenda to the current research agenda. An emerging infrastructure will require technical improvements inclusive of agreed metadata and ontologies to improve, extend and integrate the informatics tools, processes and skills to manage digital information across the full spectrum of biological phenomena. The new tools must penetrate deep into a large number of small information sources. It will require co-operation of existing enterprises, a target of service not discovery, institutional support to guarantee long term funding of the emerging infrastructure, and a considerable financial investment. 'Unifying Biology Through Informatics' will articulate, in increasing detail, the nature of an indexing infrastructure capable of evolving in response to the needs of producers and users of data; the hosting, funding and sustainability of the infrastructure, and the political and social changes needed to secure the adoption, longevity, and use of the infrastructure. The programme welcomes input on selected use-cases that can be used to identify the most pressing challenges and opportunities.

The Global Biodiversity Information Facility's 2017-2021 implementation plan includes an item with a scheduled start in 2017 to develop mechanisms to support and reflect the skills, expertise and experience of individual and organizational contributions to their network. This includes revision of their identity management system and integration of Open Researcher and Contributor IDs (ORCID). Likewise, the Joint TDWG/Research Data Alliance Interest Group on metadata standards for attribution of physical and digital collection stewardship seeks to develop metadata standards for attributing curatorial actions. Here, I propose a lightweight extension to Darwin Core to accommodate new terms for agent identifiers and their roles in the curation of physical and digital objects. In parallel, I propose shared mechanisms and codebases to help parse and disambiguate agent names in the existing Darwin Core terms: recordedBy, identifiedBy, and scientificNameAuthorship. The solutions to deal with legacy data must fit within the Biodiversity Data Quality Interest Group's recently proposed conceptual framework and be made available to individual museums, and national and international aggregators of biodiversity data. A case study using occurrence data from the Canadensys network will reveal the challenges in reconciling people names and will uncover exciting opportunities for engagement when people are shown the impact they have on their research and collections communities.

Lipid molecules can bind to specific sites on integral membrane proteins, modulating their structure and function. We have undertaken coarse-grained simulations to calculate free energy profiles for glycolipids and phospholipids interacting with modulatory sites on the transmembrane helix dimer of the EGF receptor within a lipid bilayer environment. We identify lipid interaction sites at each end of the transmembrane domain and compute interaction free energy profiles for lipids with these sites. Interaction free energies ranged from ca. −40 to −4 kJ/mol for different lipid species. Those lipids (glycolipid GM3 and phosphoinositide PIP2) known to modulate EGFR function exhibit the strongest binding to interaction sites on the EGFR, and we are able to reproduce the preference for interaction with GM3 over other glycolipids suggested by experiment. Mutation of amino acid residues essential for EGFR function reduce the binding free energy of these key lipid species. The residues interacting with the lipids in the simulations are in agreement with those suggested by experimental (mutational) studies. This approach provides a generalizable tool for characterizing the interactions of lipids that bind to specific sites on integral membrane proteins.