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This Resource describes the Image Data Resource (IDR), a prototype online system for biological image data that links experimental and analytic data across multiple data sets and promotes image data sharing and reanalysis. Access to primary research data is vital for the advancement of science. To extend the data types supported by community repositories, we built a prototype Image Data Resource (IDR). IDR links data from several imaging modalities, including high-content screening, multi-dimensional microscopy and digital pathology, with public genetic or chemical databases and cell and tissue phenotypes expressed using controlled ontologies. Using this integration, IDR facilitates the analysis of gene networks and reveals functional interactions that are inaccessible to individual studies. To enable reanalysis, we also established a computational resource based on Jupyter notebooks that allows remote access to the entire IDR. IDR is also an open-source platform for publishing imaging data. Thus IDR provides an online resource and a software infrastructure that promotes and extends publication and reanalysis of scientific image data.

We have developed a laboratory-based drug screening platform that uses a cohort of human induced pluripotent stem cell (hiPSC) lines, derived from different donors, to predict variable drug responses of potential clinical relevance. This builds on recent findings that pluripotent hiPSC lines express a broad repertoire of gene transcripts and proteins, whose expression levels reflect the genetic identity of the donor. We demonstrate that a cohort of hiPSC lines from different donors can be screened efficiently in their pluripotent state, using high-throughput Cell Painting assays. Variable phenotypic responses between hiPSC lines were detected with a wide range of clinically approved drugs, in use across multiple disease areas. Furthermore, information on mechanisms of drug-cell interactions underlying the observed variable responses was derived by using quantitative proteomic analysis to compare sets of hiPSC lines that had been stratified objectively, based upon variable response, Cell Painting data. We propose that information derived from comparative drug screening, using curated libraries of hiPSC lines from different donors, can help to improve the delivery of safe new drugs suitable for a broad range of genetic backgrounds and sexual diversity within human populations.

Imaging technologies are used throughout the life and biomedical sciences to understand mechanisms in biology and diagnosis and therapy in animal and human medicine. We present criteria for globally applicable guidelines for open image data tools and resources for the rapidly developing fields of biological and biomedical imaging.

The Type VI secretion system (T6SS) is widely used by bacterial pathogens as an effective weapon against bacterial competitors and is also deployed against host eukaryotic cells in some cases. It is a contractile nanomachine which delivers toxic effector proteins directly into target cells by dynamic cycles of assembly and firing. Bacterial cells adopt distinct post-translational regulatory strategies for deployment of the T6SS. 'Defensive' T6SSs assemble and fire in response to incoming attacks from aggressive neighbouring cells, and can utilise the Threonine Protein Phosphorylation (TPP) regulatory pathway to achieve this control. However, many T6SSs are 'offensive', firing at all-comers without the need for incoming attack or other cell contact-dependent signal. Post-translational control of the offensive mode has been less well defined but can utilise components of the same TPP pathway. Here, we used the anti-bacterial T6SS of Serratia marcescens to elucidate post-translational regulation of offensive T6SS deployment, using single-cell microscopy and genetic analyses. We show that the integration of the TPP pathway with the negative regulator TagF to control core T6SS machine assembly is conserved between offensive and defensive T6SSs. Signal-dependent PpkA-mediated phosphorylation of Fha is required to overcome inhibition of membrane complex assembly by TagF, whilst PppA-mediated dephosphorylation promotes spatial reorientation and efficient killing. In contrast, the upstream input of the TPP pathway defines regulatory strategy, with a new periplasmic regulator, RtkS, shown to interact with the PpkA kinase in S. marcescens. We propose a model whereby the opposing actions of the TPP pathway and TagF impose a delay on T6SS re-assembly after firing, providing an opportunity for spatial re-orientation of the T6SS in order to maximise the efficiency of competitor cell targeting. Our findings provide a better understanding of how bacterial cells deploy competitive weapons effectively, with implications for the structure and dynamics of varied polymicrobial communities.

Male contraceptive options and infertility treatments are limited, and almost all innovation has been limited to updates to medically assisted reproduction protocols and methods. To accelerate the development of drugs that can either improve or inhibit fertility, we established a small molecule library as a toolbox for assay development and screening campaigns using human spermatozoa. We have profiled all compounds in the Sperm Toolbox in several automated high-throughput assays that measure stimulation or inhibition of sperm motility or the acrosome reaction. We have assayed motility under non-capacitating and capacitating conditions to distinguish between pathways operating under these different physiological states. We also assayed cell viability to ensure any effects on sperm function are specific. A key advantage of our studies is that all compounds are assayed together in the same experimental conditions, which allows quantitative comparisons of their effects in complementary functional assays. We have combined the resulting datasets to generate fingerprints of the Sperm Toolbox compounds on sperm function. The data are included in an on-line R-based app for convenient querying.

Human induced pluripotent stem cells (hiPSCs) have great potential to be used as alternatives to embryonic stem cells (hESCs) in regenerative medicine and disease modelling. In this study, we characterise the proteomes of multiple hiPSC and hESC lines derived from independent donors and find that while they express a near-identical set of proteins, they show consistent quantitative differences in the abundance of a subset of proteins. hiPSCs have increased total protein content, while maintaining a comparable cell cycle profile to hESCs, with increased abundance of cytoplasmic and mitochondrial proteins required to sustain high growth rates, including nutrient transporters and metabolic proteins. Prominent changes detected in proteins involved in mitochondrial metabolism correlated with enhanced mitochondrial potential, shown using high-resolution respirometry. hiPSCs also produced higher levels of secreted proteins, including growth factors and proteins involved in the inhibition of the immune system. The data indicate that reprogramming of fibroblasts to hiPSCs produces important differences in cytoplasmic and mitochondrial proteins compared to hESCs, with consequences affecting growth and metabolism. This study improves our understanding of the molecular differences between hiPSCs and hESCs, with implications for potential risks and benefits for their use in future disease modelling and therapeutic applications.

[...]an imaging technique called focused ion beam-scanning electron microscopy (FIB-SEM) was used for decades in materials science before it was repurposed for the biosciences3. [...]FIB-SEM (used alongside other techniques for volume electron microscopy such as serial block-face SEM and array tomography) has opened a window on the inner workings of organs and organelles alike, driving a new field called connectomics (the study of the connections between brain cells to build wiring diagrams of the brain)4-7, and a surge in the number of studies reporting high-resolution 3D reconstructions of subcellular structures and organelles8. Xu et al. present data for different types of entire cell, including HeLa cells (a line of human cervical cancer cells), T cells of the immune system, and pancreatic ß-cells (which secrete the hormone insulin needed to control blood glucose levels). [...]the authors' reported results are based on whole-cell reconstructions of just three HeLa cells (two at interphase and one at the mitotic stage of the cell cycle), one example of mouse pancreatic tissue and several T cells.

Public data archives are the backbone of modern biological research. Biomolecular archives are well established, but bioimaging resources lag behind them. The technology required for imaging archives is now available, thus enabling the creation of the first public bioimage datasets. We present the rationale for the construction of bioimage archives and their associated databases to underpin the next revolution in bioinformatics discovery.

Efforts to generate nanoscale-resolution images of cell interiors have gained ground through the development and refinement of a microscopy method. The data sets are publicly available as resources for further discoveries. Refinement of a microscopy method enables a detailed look inside cells.

Recent advances in fluorescence microscopy techniques and tissue clearing, labeling, and staining provide unprecedented opportunities to investigate brain structure and function. These experiments’ images make it possible to catalog brain cell types and define their location, morphology, and connectivity in a native context, leading to a better understanding of normal development and disease etiology. Consistent annotation of metadata is needed to provide the context necessary to understand, reuse, and integrate these data. This report describes an effort to establish metadata standards for three-dimensional (3D) microscopy datasets for use by the Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative and the neuroscience research community. These standards were built on existing efforts and developed with input from the brain microscopy community to promote adoption. The resulting 3D Microscopy Metadata Standards (3D-MMS) includes 91 fields organized into seven categories: Contributors, Funders, Publication, Instrument, Dataset, Specimen, and Image. Adoption of these metadata standards will ensure that investigators receive credit for their work, promote data reuse, facilitate downstream analysis of shared data, and encourage collaboration.