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

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

Simulating structurally variable nuclear pore complexes for microscopy.

MOTIVATION: The nuclear pore complex (NPC) is the only passageway for macromolecules between nucleus and cytoplasm, and an important reference standard in microscopy: it is massive and stereotypically arranged. The average architecture of NPC proteins has been resolved with pseudoatomic precision, however observed NPC heterogeneities evidence a high degree of divergence from this average. Single-molecule localization microscopy (SMLM) images NPCs at protein-level resolution, whereupon image analysis software studies NPC variability. However, the true picture of this variability is unknown. In quantitative image analysis experiments, it is thus difficult to distinguish intrinsically high SMLM noise from variability of the underlying structure. RESULTS: We introduce CIR4MICS ('ceramics', Configurable, Irregular Rings FOR MICroscopy Simulations), a pipeline that synthesizes ground truth datasets of structurally variable NPCs based on architectural models of the true NPC. Users can select one or more N- or C-terminally tagged NPC proteins, and simulate a wide range of geometric variations. We also represent the NPC as a spring-model such that arbitrary deforming forces, of user-defined magnitudes, simulate irregularly shaped variations. Further, we provide annotated reference datasets of simulated human NPCs, which facilitate a side-by-side comparison with real data. To demonstrate, we synthetically replicate a geometric analysis of real NPC radii and reveal that a range of simulated variability parameters can lead to observed results. Our simulator is therefore valuable to test the capabilities of image analysis methods, as well as to inform experimentalists about the requirements of hypothesis-driven imaging studies. AVAILABILITY AND IMPLEMENTATION: Code: https://github.com/uhlmanngroup/cir4mics. Simulated data: BioStudies S-BSST1058.

Characterization of microglia behaviour in healthy and pathological conditions with image analysis tools.

Microglia are very sensitive to changes in the environment and respond through morphological, functional and metabolic adaptations. To depict the modifications microglia undergo under healthy and pathological conditions, we developed free access image analysis scripts to quantify microglia morphologies and phagocytosis. Neuron-glia cultures, in which microglia express the reporter tdTomato, were exposed to excitotoxicity or excitotoxicity + inflammation and analysed 8 h later. Neuronal death was assessed by SYTOX staining of nucleus debris and phagocytosis was measured through the engulfment of SYTOX+ particles in microglia. We identified seven morphologies: round, hypertrophic, fried egg, bipolar and three 'inflamed' morphologies. We generated a classifier able to separate them and assign one of the seven classes to each microglia in sample images. In control cultures, round and hypertrophic morphologies were predominant. Excitotoxicity had a limited effect on the composition of the populations. By contrast, excitotoxicity + inflammation promoted an enrichment in inflamed morphologies and increased the percentage of phagocytosing microglia. Our data suggest that inflammation is critical to promote phenotypical changes in microglia. We also validated our tools for the segmentation of microglia in brain slices and performed morphometry with the obtained mask. Our method is versatile and useful to correlate microglia sub-populations and behaviour with environmental changes.

The Image Data Explorer: Interactive exploration of image-derived data.

Many bioimage analysis projects produce quantitative descriptors of regions of interest in images. Associating these descriptors with visual characteristics of the objects they describe is a key step in understanding the data at hand. However, as many bioimage data and their analysis workflows are moving to the cloud, addressing interactive data exploration in remote environments has become a pressing issue. To address it, we developed the Image Data Explorer (IDE) as a web application that integrates interactive linked visualization of images and derived data points with exploratory data analysis methods, annotation, classification and feature selection functionalities. The IDE is written in R using the shiny framework. It can be easily deployed on a remote server or on a local computer. The IDE is available at https://git.embl.de/heriche/image-data-explorer and a cloud deployment is accessible at https://shiny-portal.embl.de/shinyapps/app/01_image-data-explorer.

Three-dimensional superresolution fluorescence microscopy maps the variable molecular architecture of the nuclear pore complex.

Nuclear pore complexes (NPCs) are large macromolecular machines that mediate the traffic between the nucleus and the cytoplasm. In vertebrates, each NPC consists of ∼1000 proteins, termed nucleoporins, and has a mass of more than 100 MDa. While a pseudo-atomic static model of the central scaffold of the NPC has recently been assembled by integrating data from isolated proteins and complexes, many structural components still remain elusive due to the enormous size and flexibility of the NPC. Here, we explored the power of three-dimensional (3D) superresolution microscopy combined with computational classification and averaging to explore the 3D structure of the NPC in single human cells. We show that this approach can build the first integrated 3D structural map containing both central as well as peripheral NPC subunits with molecular specificity and nanoscale resolution. Our unbiased classification of more than 10,000 individual NPCs indicates that the nuclear ring and the nuclear basket can adopt different conformations. Our approach opens up the exciting possibility to relate different structural states of the NPC to function in situ.

Bioimage analysis workflows: community resources to navigate through a complex ecosystem.

Workflows are the keystone of bioimage analysis, and the NEUBIAS (Network of European BioImage AnalystS) community is trying to gather the actors of this field and organize the information around them.  One of its most recent outputs is the opening of the F1000Research NEUBIAS gateway, whose main objective is to offer a channel of publication for bioimage analysis workflows and associated resources. In this paper we want to express some personal opinions and recommendations related to finding, handling and developing bioimage analysis workflows.  The emergence of "big data" in bioimaging and resource-intensive analysis algorithms make local data storage and computing solutions a limiting factor. At the same time, the need for data sharing with collaborators and a general shift towards remote work, have created new challenges and avenues for the execution and sharing of bioimage analysis workflows. These challenges are to reproducibly run workflows in remote environments, in particular when their components come from different software packages, but also to document them and link their parameters and results by following the FAIR principles (Findable, Accessible, Interoperable, Reusable) to foster open and reproducible science. In this opinion paper, we focus on giving some directions to the reader to tackle these challenges and navigate through this complex ecosystem, in order to find and use workflows, and to compare workflows addressing the same problem. We also discuss tools to run workflows in the cloud and on High Performance Computing resources, and suggest ways to make these workflows FAIR.

Tracking cells in epithelial acini by light sheet microscopy reveals proximity effects in breast cancer initiation.

Cancer clone evolution takes place within tissue ecosystem habitats. But, how exactly tumors arise from a few malignant cells within an intact epithelium is a central, yet unanswered question. This is mainly due to the inaccessibility of this process to longitudinal imaging together with a lack of systems that model the progression of a fraction of transformed cells within a tissue. Here, we developed a new methodology based on primary mouse mammary epithelial acini, where oncogenes can be switched on in single cells within an otherwise normal epithelial cell layer. We combine this stochastic breast tumor induction model with inverted light-sheet imaging to study single-cell behavior for up to four days and analyze cell fates utilizing a newly developed image-data analysis workflow. The power of this integrated approach is illustrated by us finding that small local clusters of transformed cells form tumors while isolated transformed cells do not.

There are now drugs to treat many types of cancer, but questions still remain around how these diseases start in the first place. Researchers think that tumor growth begins when a single cell suffers damage to certain sites in its DNA that eventually cause it to divide uncontrollably. That damaged cell, and its descendants, go on to form a lump, or tumor. The trouble with proving this theory is that it is hard to watch it happening in real time. Doctors usually only meet people with cancer when their tumors start to cause health problems. By this point, the tumors contain millions of cells. A way to watch the very beginnings of a cancer could reveal risk factors within a tissue that foster the growth of a tumor. But first, researchers need to test their theory about how the disease begins in the first place. One way to do this is to surround a single cancer cell with healthy cells and watch what happens next. To do this, Alladin, Chaible et al. took healthy cells from the breast tissue of mice and grew them in the laboratory into mini-organs called organoids. These organoids share a lot of features with actual mouse breast tissue; they can even make milk if given the right hormones. Once the organoids were ready, Alladin, Chaible et al then started modifying a small number of single cells inside them by switching on genes called oncogenes, which are known to drive cancer formation in humans. Using fluorescent proteins and a sheet of laser light it was possible to watch what happened to the cells over time. This revealed that, even though all the oncogene-driven single cells received the same signals, not all of them started to divide uncontrollably. In fact, a single modified cell had a low chance of forming a tumor on its own. The more oncogene-driven cells there were near to each other, the more likely they were to form tumors. Alladin, Chaible et al. think that this is because the healthy tissue interacts with the modified, oncogene-driven cells to suppress tumor formation. It is only when a larger number of modified cells group together and start to communicate with each other that they can override the inhibitory messages of the healthy tissue. How healthy tissue stops single modified cells from forming tumors is not yet clear. But, with this new mini-organ system, researchers now have the tools to investigate. In the future, this could lead to new strategies to stop cancer before it has a chance to get started.

Experimental and computational framework for a dynamic protein atlas of human cell division.

Essential biological functions, such as mitosis, require tight coordination of hundreds of proteins in space and time. Localization, the timing of interactions and changes in cellular structure are all crucial to ensure the correct assembly, function and regulation of protein complexes1-4. Imaging of live cells can reveal protein distributions and dynamics but experimental and theoretical challenges have prevented the collection of quantitative data, which are necessary for the formulation of a model of mitosis that comprehensively integrates information and enables the analysis of the dynamic interactions between the molecular parts of the mitotic machinery within changing cellular boundaries. Here we generate a canonical model of the morphological changes during the mitotic progression of human cells on the basis of four-dimensional image data. We use this model to integrate dynamic three-dimensional concentration data of many fluorescently knocked-in mitotic proteins, imaged by fluorescence correlation spectroscopy-calibrated microscopy5. The approach taken here to generate a dynamic protein atlas of human cell division is generic; it can be applied to systematically map and mine dynamic protein localization networks that drive cell division in different cell types, and can be conceptually transferred to other cellular functions.

The replicative helicase MCM recruits cohesin acetyltransferase ESCO2 to mediate centromeric sister chromatid cohesion.

Chromosome segregation depends on sister chromatid cohesion which is established by cohesin during DNA replication. Cohesive cohesin complexes become acetylated to prevent their precocious release by WAPL before cells have reached mitosis. To obtain insight into how DNA replication, cohesion establishment and cohesin acetylation are coordinated, we analysed the interaction partners of 55 human proteins implicated in these processes by mass spectrometry. This proteomic screen revealed that on chromatin the cohesin acetyltransferase ESCO2 associates with the MCM2-7 subcomplex of the replicative Cdc45-MCM-GINS helicase. The analysis of ESCO2 mutants defective in MCM binding indicates that these interactions are required for proper recruitment of ESCO2 to chromatin, cohesin acetylation during DNA replication, and centromeric cohesion. We propose that MCM binding enables ESCO2 to travel with replisomes to acetylate cohesive cohesin complexes in the vicinity of replication forks so that these complexes can be protected from precocious release by WAPL Our results also indicate that ESCO1 and ESCO2 have distinct functions in maintaining cohesion between chromosome arms and centromeres, respectively.

Correlative live and super-resolution imaging reveals the dynamic structure of replication domains.

Chromosome organization in higher eukaryotes controls gene expression, DNA replication, and DNA repair. Genome mapping has revealed the functional units of chromatin at the submegabase scale as self-interacting regions called topologically associating domains (TADs) and showed they correspond to replication domains (RDs). A quantitative structural and dynamic description of RD behavior in the nucleus is, however, missing because visualization of dynamic subdiffraction-sized RDs remains challenging. Using fluorescence labeling of RDs combined with correlative live and super-resolution microscopy in situ, we determined biophysical parameters to characterize the internal organization, spacing, and mechanical coupling of RDs. We found that RDs are typically 150 nm in size and contain four co-replicating regions spaced 60 nm apart. Spatially neighboring RDs are spaced 300 nm apart and connected by highly flexible linker regions that couple their motion only <550 nm. Our pipeline allows a robust quantitative characterization of chromosome structure in situ and provides important biophysical parameters to understand general principles of chromatin organization.

Postmitotic nuclear pore assembly proceeds by radial dilation of small membrane openings.

The nuclear envelope has to be reformed after mitosis to create viable daughter cells with closed nuclei. How membrane sealing of DNA and assembly of nuclear pore complexes (NPCs) are achieved and coordinated is poorly understood. Here, we reconstructed nuclear membrane topology and the structures of assembling NPCs in a correlative 3D EM time course of dividing human cells. Our quantitative ultrastructural analysis shows that nuclear membranes form from highly fenestrated ER sheets whose holes progressively shrink. NPC precursors are found in small membrane holes and dilate radially during assembly of the inner ring complex, forming thousands of transport channels within minutes. This mechanism is fundamentally different from that of interphase NPC assembly and explains how mitotic cells can rapidly establish a closed nuclear compartment while making it transport competent.

Identifiers for the 21st century: How to design, provision, and reuse persistent identifiers to maximize utility and impact of life science data.

In many disciplines, data are highly decentralized across thousands of online databases (repositories, registries, and knowledgebases). Wringing value from such databases depends on the discipline of data science and on the humble bricks and mortar that make integration possible; identifiers are a core component of this integration infrastructure. Drawing on our experience and on work by other groups, we outline 10 lessons we have learned about the identifier qualities and best practices that facilitate large-scale data integration. Specifically, we propose actions that identifier practitioners (database providers) should take in the design, provision and reuse of identifiers. We also outline the important considerations for those referencing identifiers in various circumstances, including by authors and data generators. While the importance and relevance of each lesson will vary by context, there is a need for increased awareness about how to avoid and manage common identifier problems, especially those related to persistence and web-accessibility/resolvability. We focus strongly on web-based identifiers in the life sciences; however, the principles are broadly relevant to other disciplines.

How can functional annotations be derived from profiles of phenotypic annotations?

BACKGROUND: Loss-of-function phenotypes are widely used to infer gene function using the principle that similar phenotypes are indicative of similar functions. However, converting phenotypic to functional annotations requires careful interpretation of phenotypic descriptions and assessment of phenotypic similarity. Understanding how functions and phenotypes are linked will be crucial for the development of methods for the automatic conversion of gene loss-of-function phenotypes to gene functional annotations. RESULTS: We explored the relation between cellular phenotypes from RNAi-based screens in human cells and gene annotations of cellular functions as provided by the Gene Ontology (GO). Comparing different similarity measures, we found that information content-based measures of phenotypic similarity were the best at capturing gene functional similarity. However, phenotypic similarities did not map to the Gene Ontology organization of gene function but to functions defined as groups of GO terms with shared gene annotations. CONCLUSIONS: Our observations have implications for the use and interpretation of phenotypic similarities as a proxy for gene functions both in RNAi screen data analysis and curation and in the prediction of disease genes.

Profiling DNA damage response following mitotic perturbations.

Genome integrity relies on precise coordination between DNA replication and chromosome segregation. Whereas replication stress attracted much attention, the consequences of mitotic perturbations for genome integrity are less understood. Here, we knockdown 47 validated mitotic regulators to show that a broad spectrum of mitotic errors correlates with increased DNA breakage in daughter cells. Unexpectedly, we find that only a subset of these correlations are functionally linked. We identify the genuine mitosis-born DNA damage events and sub-classify them according to penetrance of the observed phenotypes. To demonstrate the potential of this resource, we show that DNA breakage after cytokinesis failure is preceded by replication stress, which mounts during consecutive cell cycles and coincides with decreased proliferation. Together, our results provide a resource to gauge the magnitude and dynamics of DNA breakage associated with mitotic aberrations and suggest that replication stress might limit propagation of cells with abnormal karyotypes.

The cellular microscopy phenotype ontology.

BACKGROUND: Phenotypic data derived from high content screening is currently annotated using free-text, thus preventing the integration of independent datasets, including those generated in different biological domains, such as cell lines, mouse and human tissues. DESCRIPTION: We present the Cellular Microscopy Phenotype Ontology (CMPO), a species neutral ontology for describing phenotypic observations relating to the whole cell, cellular components, cellular processes and cell populations. CMPO is compatible with related ontology efforts, allowing for future cross-species integration of phenotypic data. CMPO was developed following a curator-driven approach where phenotype data were annotated by expert biologists following the Entity-Quality (EQ) pattern. These EQs were subsequently transformed into new CMPO terms following an established post composition process. CONCLUSION: CMPO is currently being utilized to annotate phenotypes associated with high content screening datasets stored in several image repositories including the Image Data Repository (IDR), MitoSys project database and the Cellular Phenotype Database to facilitate data browsing and discoverability.

ARHGEF17 is an essential spindle assembly checkpoint factor that targets Mps1 to kinetochores.

To prevent genome instability, mitotic exit is delayed until all chromosomes are properly attached to the mitotic spindle by the spindle assembly checkpoint (SAC). In this study, we characterized the function of ARHGEF17, identified in a genome-wide RNA interference screen for human mitosis genes. Through a series of quantitative imaging, biochemical, and biophysical experiments, we showed that ARHGEF17 is essential for SAC activity, because it is the major targeting factor that controls localization of the checkpoint kinase Mps1 to the kinetochore. This mitotic function is mediated by direct interaction of the central domain of ARHGEF17 with Mps1, which is autoregulated by the activity of Mps1 kinase, for which ARHGEF17 is a substrate. This mitosis-specific role is independent of ARHGEF17's RhoGEF activity in interphase. Our study thus assigns a new mitotic function to ARHGEF17 and reveals the molecular mechanism for a key step in SAC establishment.

FUN-L: gene prioritization for RNAi screens.

MOTIVATION: Most biological processes remain only partially characterized with many components still to be identified. Given that a whole genome can usually not be tested in a functional assay, identifying the genes most likely to be of interest is of critical importance to avoid wasting resources. RESULTS: Given a set of known functionally related genes and using a state-of-the-art approach to data integration and mining, our Functional Lists (FUN-L) method provides a ranked list of candidate genes for testing. Validation of predictions from FUN-L with independent RNAi screens confirms that FUN-L-produced lists are enriched in genes with the expected phenotypes. In this article, we describe a website front end to FUN-L. AVAILABILITY AND IMPLEMENTATION: The website is freely available to use at http://funl.org