Assessing 2D visual encoding of 3D spatial connectivity.

Introduction: When visualizing complex data, the layout method chosen can greatly affect the ability to identify outliers, spot incorrect modeling assumptions, or recognize unexpected patterns. Additionally, visual layout can play a crucial role in communicating results to peers. Methods: In this paper, we compared the effectiveness of three visual layouts-the adjacency matrix, a half-matrix layout, and a circular layout-for visualizing spatial connectivity data, e.g., contacts derived from chromatin conformation capture experiments. To assess these visual layouts, we conducted a study comprising 150 participants from Amazon's Mechanical Turk, as well as a second expert study comprising 30 biomedical research scientists. Results: The Mechanical Turk study found that the circular layout was the most accurate and intuitive, while the expert study found that the circular and half-matrix layouts were more accurate than the matrix layout. Discussion: We concluded that the circular layout may be a good default choice for visualizing smaller datasets with relatively few spatial contacts, while, for larger datasets, the half- matrix layout may be a better choice. Our results also demonstrated how crowdsourcing methods could be used to determine which visual layouts are best for addressing specific data challenges in bioinformatics.

Increased core body temperature exacerbates defective protein prenylation in mouse models of mevalonate kinase deficiency.

Mevalonate kinase deficiency (MKD) is characterized by recurrent fevers and flares of systemic inflammation, caused by biallelic loss-of-function mutations in MVK. The underlying disease mechanisms and triggers of inflammatory flares are poorly understood because of the lack of in vivo models. We describe genetically modified mice bearing the hypomorphic mutation p.Val377Ile (the commonest variant in patients with MKD) and amorphic, frameshift mutations in Mvk. Compound heterozygous mice recapitulated the characteristic biochemical phenotype of MKD, with increased plasma mevalonic acid and clear buildup of unprenylated GTPases in PBMCs, splenocytes, and bone marrow. The inflammatory response to LPS was enhanced in compound heterozygous mice and treatment with the NLRP3 inflammasome inhibitor MCC950 prevented the elevation of circulating IL-1ß, thus identifying a potential inflammasome target for future therapeutic approaches. Furthermore, lines of mice with a range of deficiencies in mevalonate kinase and abnormal prenylation mirrored the genotype-phenotype relationship in human MKD. Importantly, these mice allowed the determination of a threshold level of residual enzyme activity, below which protein prenylation is impaired. Elevated temperature dramatically but reversibly exacerbated the deficit in the mevalonate pathway and the defective prenylation in vitro and in vivo, highlighting increased body temperature as a likely trigger of inflammatory flares.

A roadmap for the functional annotation of protein families: a community perspective.

Over the last 25 years, biology has entered the genomic era and is becoming a science of 'big data'. Most interpretations of genomic analyses rely on accurate functional annotations of the proteins encoded by more than 500 000 genomes sequenced to date. By different estimates, only half the predicted sequenced proteins carry an accurate functional annotation, and this percentage varies drastically between different organismal lineages. Such a large gap in knowledge hampers all aspects of biological enterprise and, thereby, is standing in the way of genomic biology reaching its full potential. A brainstorming meeting to address this issue funded by the National Science Foundation was held during 3-4 February 2022. Bringing together data scientists, biocurators, computational biologists and experimentalists within the same venue allowed for a comprehensive assessment of the current state of functional annotations of protein families. Further, major issues that were obstructing the field were identified and discussed, which ultimately allowed for the proposal of solutions on how to move forward.

Collaborative Sense-Making in Genomic Research: The Role of Visualisation.

Genomic research emerges from collaborative work within and across different scientific disciplines. A diverse range of visualisation techniques has been employed to aid this research, yet relatively little is known as to how these techniques facilitate collaboration. We conducted a case study of collaborative research within a biomedical institute to learn more about the role visualisation plays in genomic mapping. Interviews were conducted with molecular biologists (N = 5) and bioinformaticians (N = 6). We found that genomic research comprises a variety of distinct disciplines engaged in complex analytic tasks that each resist simplification, and their complexity influences how visualisations were used. Visualisation use was impacted by group-specific interactions and temporal work patterns. Visualisations were also crucial to the scientific workflow, used for both question formation and confirmation of hypotheses, and acted as an anchor for the communication of ideas and discussion. In the latter case, two approaches were taken: providing collaborators with either interactive or static imagery representing a viewpoint. The use of generic software for simplified visualisations, and quick production and curation was also noted. We discuss these findings with reference to group-specific interactions and present recommendations for improving collaborative practices through visual analytics.

SARS-CoV-2 structural coverage map reveals viral protein assembly, mimicry, and hijacking mechanisms.

We modeled 3D structures of all SARS-CoV-2 proteins, generating 2,060 models that span 69% of the viral proteome and provide details not available elsewhere. We found that ˜6% of the proteome mimicked human proteins, while ˜7% was implicated in hijacking mechanisms that reverse post-translational modifications, block host translation, and disable host defenses; a further ˜29% self-assembled into heteromeric states that provided insight into how the viral replication and translation complex forms. To make these 3D models more accessible, we devised a structural coverage map, a novel visualization method to show what is-and is not-known about the 3D structure of the viral proteome. We integrated the coverage map into an accompanying online resource (https://aquaria.ws/covid) that can be used to find and explore models corresponding to the 79 structural states identified in this work. The resulting Aquaria-COVID resource helps scientists use emerging structural data to understand the mechanisms underlying coronavirus infection and draws attention to the 31% of the viral proteome that remains structurally unknown or dark.

Democratizing epilepsy care: Utility and usability of an electronic patient portal.

OBJECTIVES: Electronic patient portals (ePortals) can facilitate greater healthcare democratization by providing patients and/or their authorized care partners with secure access to their medical records when and where needed. Such democratization can promote effective healthcare provider-patient partnerships, shared decision-making, and greater patient engagement in managing their health condition. This study examined the usefulness of providing individualized services and care in epilepsy (PiSCES), an epilepsy ePortal, as an enabler of more democratized epilepsy care. METHODS: Seventy-two individuals with epilepsy and 18 care partners were invited to report on their experience of interacting via PiSCES with clinical documents (epilepsy care summary record; epilepsy clinic letters) authored about them by healthcare providers. The OpenNotes reporting tool was adapted to capture participant experience. RESULTS: Twenty-five percent of invited patients and 44% of invited care partners reported on interacting with their epilepsy care summary; 14% of patients and 67% of care partners invited reported on their epilepsy clinic letters. Participant testimonials illustrate the value of PiSCES in: promoting autonomy, aiding memory, developing the knowledgeable patient, and enhancing healthcare partnerships. Ninety-six percent and 100% of respondents, respectively, reported understanding their epilepsy care summary and epilepsy clinic letter; 77% said the summary described their epilepsy history to date; 96% indicated that the letter provided an accurate description of their clinical encounter; 92% and 96%, respectively, valued access to their summary record and clinic letters; 77% of summary record and 73% clinic letter respondents reported learning something about their epilepsy or the healthcare service via PiSCES. Illustrating their potential patient and care partner safety role, 42% respondents identified inaccuracies in their clinical documents which were subsequently resolved by a clinician. SIGNIFICANCE: In the post-digital world highly customized on-demand products and services have come to be expected. Similarly, in epilepsy care, technologies such as PiSCES can enable more personalized, transparent, and engaging services.

PredictProtein - Predicting Protein Structure and Function for 29 Years.

Since 1992 PredictProtein (https://predictprotein.org) is a one-stop online resource for protein sequence analysis with its main site hosted at the Luxembourg Centre for Systems Biomedicine (LCSB) and queried monthly by over 3,000 users in 2020. PredictProtein was the first Internet server for protein predictions. It pioneered combining evolutionary information and machine learning. Given a protein sequence as input, the server outputs multiple sequence alignments, predictions of protein structure in 1D and 2D (secondary structure, solvent accessibility, transmembrane segments, disordered regions, protein flexibility, and disulfide bridges) and predictions of protein function (functional effects of sequence variation or point mutations, Gene Ontology (GO) terms, subcellular localization, and protein-, RNA-, and DNA binding). PredictProtein's infrastructure has moved to the LCSB increasing throughput; the use of MMseqs2 sequence search reduced runtime five-fold (apparently without lowering performance of prediction methods); user interface elements improved usability, and new prediction methods were added. PredictProtein recently included predictions from deep learning embeddings (GO and secondary structure) and a method for the prediction of proteins and residues binding DNA, RNA, or other proteins. PredictProtein.org aspires to provide reliable predictions to computational and experimental biologists alike. All scripts and methods are freely available for offline execution in high-throughput settings.

Single-cell transcriptomics reveals involution mimicry during the specification of the basal breast cancer subtype.

Basal breast cancer is associated with younger age, early relapse, and a high mortality rate. Here, we use unbiased droplet-based single-cell RNA sequencing (RNA-seq) to elucidate the cellular basis of tumor progression during the specification of the basal breast cancer subtype from the luminal progenitor population in the MMTV-PyMT (mouse mammary tumor virus-polyoma middle tumor-antigen) mammary tumor model. We find that basal-like cancer cells resemble the alveolar lineage that is specified upon pregnancy and encompass the acquisition of an aberrant post-lactation developmental program of involution that triggers remodeling of the tumor microenvironment and metastatic dissemination. This involution mimicry is characterized by a highly interactive multicellular network, with involution cancer-associated fibroblasts playing a pivotal role in extracellular matrix remodeling and immunosuppression. Our results may partially explain the increased risk and poor prognosis of breast cancer associated with childbirth.

Coproducing health and well-being in partnership with patients, families, and healthcare providers: A qualitative study exploring the role of an epilepsy patient portal.

BACKGROUND: Coproduced epilepsy care sees people with epilepsy (PwE), their care-proxies, and healthcare providers (HCPs), working together as partners to build strong relationships, improve communication, trust, and share decision-making. Coproduction underpins good quality patient- and family-centered care (PFCC) that is responsive to individual patient needs, preferences, and values. By facilitating information sharing and exchange between partners, electronic patient portals (ePortal) can enable coproduction. This paper explores what HCPs, PwE, and their care-proxies value from their user experience of PiSCES, the Irish epilepsy ePortal. METHODS: A purposeful sample of actors involved in the receipt and delivery of epilepsy care and services were recruited via adult epilepsy centers at St James's and Beaumont Hospitals in Dublin. Interactive codesign sessions, surveys, and focus groups were used to elicit perspectives from PwE, care-proxies, and HCPs to understand their perception of how PiSCES could enhance or inhibit the epilepsy care process. RESULTS: Results illustrate that participants welcome the role PiSCES can play in: empowering PwE/care-proxies, strengthening confidence in the healthcare system; aiding memory; advancing health literacy, motivating PwE to understand their condition better; acting as a passport of care between different clinical settings; and creating a foundation for stronger coproduction partnerships. PiSCES was generally embraced; however, some HCPs expressed plausible concerns about how clinical implementation might impact their work practices. CONCLUSION: "Nothing about me without me" is a core value of the PiSCES initiative, recognizing that people need to be included in the planning of their own treatment and care. Our data show that PwE, their care-proxies, and HCPs value PiSCES potential, particularly in bolstering healthcare partnerships that foster inclusion, confidence, and trust.

Temporal ordering of omics and multiomic events inferred from time-series data.

Temporal changes in omics events can now be routinely measured; however, current analysis methods are often inadequate, especially for multiomics experiments. We report a novel analysis method that can infer event ordering at better temporal resolution than the experiment, and integrates omic events into two concise visualizations (event maps and sparklines). Testing our method gave results well-correlated with prior knowledge and indicated it streamlines analysis of time-series data.

The development of an epilepsy electronic patient portal: Facilitating both patient empowerment and remote clinician-patient interaction in a post-COVID-19 world.

OBJECTIVES: The current coronavirus disease 2019 (COVID-19) pandemic stresses an urgency to accelerate much-needed health service reform. Rapid and courageous changes being made to address the immediate impact of the pandemic are demonstrating that the means and technology to enable new models of health care exist. For example, innovations such as electronic patient portals (ePortal) can facilitate (a) radical reform of outpatient care; (b) cost containment in the economically constrained aftermath of the pandemic; (c) environmental sustainability by reduction of unnecessary journeys/transport. Herein, the development of Providing Individualised Services and Care in Epilepsy (PiSCES), an ePortal to the Irish National Epilepsy Electronic Patient Record, is demonstrated. This project, which pre-dates the COVID-19 crisis, aims to facilitate better patient- and family-centered epilepsy care. METHODS: A combination of ethnographic research, document analysis, and joint application design sessions was used to elicit PiSCES requirements. From these, a specification of desired modules of functionality was established and guided the software development. RESULTS: PiSCES functional features include "My Epilepsy Care Summary," "My Epilepsy Care Goals," "My Epilepsy Clinic Letters," "Help Us Measure Your Progress," "Prepare For Your Clinic Visit," "Information for Your Healthcare Provider." The system provides people with epilepsy access to, and engages them as co-authors of, their own medical record. It can promote improved patient-clinician partnerships and facilitate patient self-management. SIGNIFICANCE: In the aftermath of COVID-19, it is highly unlikely that the healthcare sector will return to a "business as usual" way of delivering services. The pandemic is expected to accelerate adoption of innovations like PiSCES. It is therefore a catalyst for change that will deliver care that is more responsive to individual patient needs and preferences.

Molecular Graphics: Bridging Structural Biologists and Computer Scientists.

Visualization of molecular structures is one of the most common tasks carried out by structural biologists, typically using software, such as Chimera, COOT, PyMOL, or VMD. In this Perspective article, we outline how past developments in computer graphics and data visualization have expanded the understanding of biomolecular function, and we summarize recent advances that promise to further transform structural biology. We also highlight how progress in molecular graphics has been impeded by communication barriers between two communities: the computer scientists driving these advances, and the structural and computational biologists who stand to benefit. By pointing to canonical papers and explaining technical progress underlying new graphical developments in simple terms, we aim to improve communication between these communities; this, in turn, would help shape future developments in molecular graphics.

SnapShot: S-Phase Entry and Exit.

S-phase entry and exit are regulated by hundreds of protein complexes that assemble "just in time," orchestrated by a multitude of distinct events. To help understand their interplay, we have created a tailored visualization based on the Minardo layout, highlighting over 80 essential events. This complements our earlier visualization of M-phase, and both can be displayed together, giving a comprehensive overview of the events regulating the cell division cycle. To view this SnapShot, open or download the PDF.

A benchmark dataset for analyzing and visualizing the dynamic epiproteome.

In this paper, we present a benchmark dataset to evaluate the currently available analysis methods and visualizations for epiproteomic data. The benchmark dataset is a subset of a high-throughput time-series study of phosphoevents occurring upon insulin stimulation. Our dataset is provided in multiple formats for use with four currently available tools. We also provide a file containing the kinase assignments for the sites, as well as a simple kappa model on phosphorylation changes in insulin signalling. A detailed description of the tools, their analysis methods, and the visualizations generated using the input files described here, are discussed in detail in the accompanying review titled "Visualization and analysis of epiproteome dynamics" [1].

Visualization and Analysis of Epiproteome Dynamics.

The epiproteome describes the set of all post-translational modifications (PTMs) made to the proteins comprising a cell or organism. The extent of the epiproteome is still largely unknown; however, advances in experimental techniques are beginning to produce a deluge of data, tracking dynamic changes to the epiproteome in response to cellular stimuli. These data have potential to revolutionize our understanding of biology and disease. This review covers a range of recent visualization methods and tools developed specifically for dynamic epiproteome data sets. These methods have been designed primarily for data sets on phosphorylation, as this the most studied PTM; however, most of these methods are also applicable to other types of PTMs. Unfortunately, the currently available methods are often inadequate for existing data sets; thus, realizing the potential buried in epiproteome data sets will require new, tailored bioinformatics methods that will help researchers analyze, visualize, and interactively explore these complex data sets.

Dark Proteins Important for Cellular Function.

Despite substantial and successful projects for structural genomics, many proteins remain for which neither experimental structures nor homology-based models are known for any part of the amino acid sequence. These have been called "dark proteins," in contrast to non-dark proteins, in which at least part of the sequence has a known or inferred structure. It has been hypothesized that non-dark proteins may be more abundantly expressed than dark proteins, which are known to have much fewer sequence relatives. Surprisingly, the opposite has been observed: human dark and non-dark proteins had quite similar levels of expression, in terms of both mRNA and protein abundance. Such high levels of expression strongly indicate that dark proteins-as a group-are important for cellular function. This is remarkable, given how carefully structural biologists have focused on proteins crucial for function, and highlights the important challenge posed by dark proteins in future research.

The Dark Proteome Database.

BACKGROUND: Recently we surveyed the dark-proteome, i.e., regions of proteins never observed by experimental structure determination and inaccessible to homology modelling. Surprisingly, we found that most of the dark proteome could not be accounted for by conventional explanations (e.g., intrinsic disorder, transmembrane domains, and compositional bias), and that nearly half of the dark proteome comprised dark proteins, in which the entire sequence lacked similarity to any known structure. In this paper we will present the Dark Proteome Database (DPD) and associated web services that provide access to updated information about the dark proteome. RESULTS: We assembled DPD from several external web resources (primarily Aquaria and Swiss-Prot) and stored it in a relational database currently containing ~10 million entries and occupying ~2 GBytes of disk space. This database comprises two key tables: one giving information on the 'darkness' of each protein, and a second table that breaks each protein into dark and non-dark regions. In addition, a second version of the database is created using also information from the Protein Model Portal (PMP) to determine darkness. To provide access to DPD, a web server has been implemented giving access to all underlying data, as well as providing access to functional analyses derived from these data. CONCLUSIONS: Availability of this database and its web service will help focus future structural and computational biology efforts to study the dark proteome, thus providing a basis for understanding a wide variety of biological functions that currently remain unknown. AVAILABILITY AND IMPLEMENTATION: DPD is available at http://darkproteome.ws. The complete database is also available upon request. Data use is permitted via the Creative Commons Attribution-NonCommercial International license (http://creativecommons.org/licenses/by-nc/4.0/).

SnapShot: Phosphoregulation of Mitosis.

During mitosis, a cell divides its duplicated genome into two identical daughter cells. This process must occur without errors to prevent proliferative diseases (e.g., cancer). A key mechanism controlling mitosis is the precise timing of more than 32,000 phosphorylation and dephosphorylation events by a network of kinases and counterbalancing phosphatases. The identity, magnitude, and temporal regulation of these events have emerged recently, largely from advances in mass spectrometry. Here, we show phosphoevents currently believed to be key regulators of mitosis. For an animated version of this SnapShot, please see http://www.cell.com/cell/enhanced/odonoghue2.

Monogenic and polygenic determinants of sarcoma risk: an international genetic study.

BACKGROUND: Sarcomas are rare, phenotypically heterogeneous cancers that disproportionately affect the young. Outside rare syndromes, the nature, extent, and clinical significance of their genetic origins are not known. We aimed to investigate the genetic basis for bone and soft-tissue sarcoma seen in routine clinical practice. METHODS: In this genetic study, we included 1162 patients with sarcoma from four cohorts (the International Sarcoma Kindred Study [ISKS], 966 probands; Project GENESIS, 48 probands; Asan Bio-Resource Center, 138 probands; and kConFab, ten probands), who were older than 15 years at the time of consent and had a histologically confirmed diagnosis of sarcoma, recruited from specialist sarcoma clinics without regard to family history. Detailed clinical, pathological, and pedigree information was collected, and cancer diagnoses in probands and relatives were independently verified. Targeted exon sequencing using blood (n=1114) or saliva (n=48) samples was done on 72 genes (selected due to associations with increased cancer risk) and rare variants were stratified into classes approximating the International Agency for Research on Cancer (IARC) clinical classification for genetic variation. We did a case-control rare variant burden analysis using 6545 Caucasian controls included from three cohorts (ISKS, 235 controls; LifePool, 2010 controls; and National Heart, Lung, and Blood Institute Exome Sequencing Project [ESP], 4300 controls). FINDINGS: The median age at cancer diagnosis in 1162 sarcoma probands was 46 years (IQR 29-58), 170 (15%) of 1162 probands had multiple primary cancers, and 155 (17%) of 911 families with informative pedigrees fitted recognisable cancer syndromes. Using a case-control rare variant burden analysis, 638 (55%) of 1162 sarcoma probands bore an excess of pathogenic germline variants (combined odds ratio [OR] 1·43, 95% CI 1·24-1·64, p<0·0001), with 227 known or expected pathogenic variants occurring in 217 individuals. All classes of pathogenic variants (known, expected, or predicted) were associated with earlier age of cancer onset. In addition to TP53, ATM, ATR, and BRCA2, an unexpected excess of functionally pathogenic variants was seen in ERCC2. Probands were more likely than controls to have multiple pathogenic variants compared with the combined control cohort group and the LifePool control cohort (OR 2·22, 95% CI 1·57-3·14, p=1·2 × 10(-6)) and the cumulative burden of multiple variants correlated with earlier age at cancer diagnosis (Mantel-Cox log-rank test for trend, p=0·0032). 66 of 1162 probands carried notifiable variants following expert clinical review (those recognised to be clinically significant to health and about which patients should be advised), whereas 293 (25%) probands carried variants with potential therapeutic significance. INTERPRETATION: About half of patients with sarcoma have putatively pathogenic monogenic and polygenic variation in known and novel cancer genes, with implications for risk management and treatment. FUNDING: Rainbows for Kate Foundation, Johanna Sewell Research Foundation, Australian National Health and Medical Research Council, Cancer Australia, Sarcoma UK, National Cancer Institute, Liddy Shriver Sarcoma Initiative.