Label-free segmentation of co-cultured cells on a nanotopographical gradient

The function and fate of cells is influenced by many different factors, one of which is surface topography of the support culture substrate. Systematic studies of nanotopography and cell response have typically been limited to single cell types and a small set of topographical variations. Here, we show a radical expansion of experimental throughput using automated detection, measurement, and classification of co-cultured cells on a nanopillar array where feature height changes continuously from planar to 250 nm over 9 mm. Individual cells are identified and characterized by more than 200 descriptors, which are used to construct a set of rules for label-free segmentation into individual cell types. Using this approach we can achieve label-free segmentation with 84% confidence across large image data sets and suggest optimized surface parameters for nanostructuring of implant devices such as vascular stents

Microscopy-BIDS: An extension to the brain imaging data structure for microscopy data

The Brain Imaging Data Structure (BIDS) is a specification for organizing, sharing, and archiving neuroimaging data and metadata in a reusable way. First developed for magnetic resonance imaging (MRI) datasets, the community-led specification evolved rapidly to include other modalities such as magnetoencephalography, positron emission tomography, and quantitative MRI (qMRI). In this work, we present an extension to BIDS for microscopy imaging data, along with example datasets. Microscopy-BIDS supports common imaging methods, including 2D/3D, ex/in vivo, micro-CT, and optical and electron microscopy. Microscopy-BIDS also includes comprehensible metadata definitions for hardware, image acquisition, and sample properties. This extension will facilitate future harmonization efforts in the context of multi-modal, multi-scale imaging such as the characterization of tissue microstructure with qMRI

QSAR-Driven Discovery of Novel Chemical Scaffolds Active against Schistosoma mansoni.

Schistosomiasis is a neglected tropical disease that affects millions of people worldwide. Thioredoxin glutathione reductase of Schistosoma mansoni (SmTGR) is a validated drug target that plays a crucial role in the redox homeostasis of the parasite. We report the discovery of new chemical scaffolds against S. mansoni using a combi-QSAR approach followed by virtual screening of a commercial database and confirmation of top ranking compounds by in vitro experimental evaluation with automated imaging of schistosomula and adult worms. We constructed 2D and 3D quantitative structure-activity relationship (QSAR) models using a series of oxadiazoles-2-oxides reported in the literature as SmTGR inhibitors and combined the best models in a consensus QSAR model. This model was used for a virtual screening of Hit2Lead set of ChemBridge database and allowed the identification of ten new potential SmTGR inhibitors. Further experimental testing on both shistosomula and adult worms showed that 4-nitro-3,5-bis(1-nitro-1H-pyrazol-4-yl)-1H-pyrazole (LabMol-17) and 3-nitro-4-{[(4-nitro-1,2,5-oxadiazol-3-yl)oxy]methyl}-1,2,5-oxadiazole (LabMol-19), two compounds representing new chemical scaffolds, have high activity in both systems. These compounds will be the subjects for additional testing and, if necessary, modification to serve as new schistosomicidal agents

Label-free cell cycle analysis for high-throughput imaging flow cytometry

Imaging flow cytometry combines the high-throughput capabilities of conventional flow cytometry with single-cell imaging. Here we demonstrate label-free prediction of DNA content and quantification of the mitotic cell cycle phases by applying supervised machine learning to morphological features extracted from brightfield and the typically ignored darkfield images of cells from an imaging flow cytometer. This method facilitates non-destructive monitoring of cells avoiding potentially confounding effects of fluorescent stains while maximizing available fluorescence channels. The method is effective in cell cycle analysis for mammalian cells, both fixed and live, and accurately assesses the impact of a cell cycle mitotic phase blocking agent. As the same method is effective in predicting the DNA content of fission yeast, it is likely to have a broad application to other cell types

Crowdsourcing the creation of image segmentation algorithms for connectomics

To stimulate progress in automating the reconstruction of neural circuits, we organized the first international challenge on 2D segmentation of electron microscopic (EM) images of the brain. Participants submitted boundary maps predicted for a test set of images, and were scored based on their agreement with a consensus of human expert annotations. The winning team had no prior experience with EM images, and employed a convolutional network. This “deep learning” approach has since become accepted as a standard for segmentation of EM images. The challenge has continued to accept submissions, and the best so far has resulted from cooperation between two teams. The challenge has probably saturated, as algorithms cannot progress beyond limits set by ambiguities inherent in 2D scoring and the size of the test dataset. Retrospective evaluation of the challenge scoring system reveals that it was not sufficiently robust to variations in the widths of neurite borders. We propose a solution to this problem, which should be useful for a future 3D segmentation challenge

Microscopy-BIDS: An Extension to the Brain Imaging Data Structure for Microscopy Data

The Brain Imaging Data Structure (BIDS) is a specification for organizing, sharing, and archiving neuroimaging data and metadata in a reusable way. First developed for magnetic resonance imaging (MRI) datasets, the community-led specification evolved rapidly to include other modalities such as magnetoencephalography, positron emission tomography, and quantitative MRI (qMRI). In this work, we present an extension to BIDS for microscopy imaging data, along with example datasets. Microscopy-BIDS supports common imaging methods, including 2D/3D, ex/in vivo, micro-CT, and optical and electron microscopy. Microscopy-BIDS also includes comprehensible metadata definitions for hardware, image acquisition, and sample properties. This extension will facilitate future harmonization efforts in the context of multi-modal, multi-scale imaging such as the characterization of tissue microstructure with qMRI

Intradermal Indocyanine Green for In Vivo Fluorescence Laser Scanning Microscopy of Human Skin: A Pilot Study

BACKGROUND: In clinical diagnostics, as well as in routine dermatology, the increased need for non-invasive diagnosis is currently satisfied by reflectance laser scanning microscopy. However, this technique has some limitations as it relies solely on differences in the reflection properties of epidermal and dermal structures. To date, the superior method of fluorescence laser scanning microscopy is not generally applied in dermatology and predominantly restricted to fluorescein as fluorescent tracer, which has a number of limitations. Therefore, we searched for an alternative fluorophore matching a novel skin imaging device to advance this promising diagnostic approach. METHODOLOGY/PRINCIPAL FINDINGS: Using a Vivascope®-1500 Multilaser microscope, we found that the fluorophore Indocyanine-Green (ICG) is well suited as a fluorescent marker for skin imaging in vivo after intradermal injection. ICG is one of few fluorescent dyes approved for use in humans. Its fluorescence properties are compatible with the application of a near-infrared laser, which penetrates deeper into the tissue than the standard 488 nm laser for fluorescein. ICG-fluorescence turned out to be much more stable than fluorescein in vivo, persisting for more than 48 hours without significant photobleaching whereas fluorescein fades within 2 hours. The well-defined intercellular staining pattern of ICG allows automated cell-recognition algorithms, which we accomplished with the free software CellProfiler, providing the possibility of quantitative high-content imaging. Furthermore, we demonstrate the superiority of ICG-based fluorescence microscopy for selected skin pathologies, including dermal nevi, irritant contact dermatitis and necrotic skin. CONCLUSIONS/SIGNIFICANCE: Our results introduce a novel in vivo skin imaging technique using ICG, which delivers a stable intercellular fluorescence signal ideal for morphological assessment down to sub-cellular detail. The application of ICG in combination with the near infrared laser opens new ways for minimal-invasive diagnosis and monitoring of skin disorders

Imaging aspects of cardiovascular disease at the cell and molecular level

Cell and molecular imaging has a long and distinguished history. Erythrocytes were visualized microscopically by van Leeuwenhoek in 1674, and microscope technology has evolved mightily since the first single-lens instruments, and now incorporates many types that do not use photons of light for image formation. The combination of these instruments with preparations stained with histochemical and immunohistochemical markers has revolutionized imaging by allowing the biochemical identification of components at subcellular resolution. The field of cardiovascular disease has benefited greatly from these advances for the characterization of disease etiologies. In this review, we will highlight and summarize the use of microscopy imaging systems, including light microscopy, electron microscopy, confocal scanning laser microscopy, laser scanning cytometry, laser microdissection, and atomic force microscopy in conjunction with a variety of histochemical techniques in studies aimed at understanding mechanisms underlying cardiovascular diseases at the cell and molecular level

Rational design and validation of a Tip60 histone acetyltransferase inhibitor

Histone acetylation is required for many aspects of gene regulation, genome maintenance and metabolism and dysfunctional acetylation is implicated in numerous diseases, including cancer. Acetylation is regulated by histone acetyltransferases (HATs) and histone deacetylases and currently, few general HAT inhibitors have been described. We identified the HAT Tip60 as an excellent candidate for targeted drug development, as Tip60 is a key mediator of the DNA damage response and transcriptional co-activator. Our modeling of Tip60 indicated that the active binding pocket possesses opposite charges at each end, with the positive charges attributed to two specific side chains. We used structure based drug design to develop a novel Tip60 inhibitor, TH1834, to fit this specific pocket. We demonstrate that TH1834 significantly inhibits Tip60 activity in vitro and treating cells with TH1834 results in apoptosis and increased unrepaired DNA damage (following ionizing radiation treatment) in breast cancer but not control cell lines. Furthermore, TH1834 did not affect the activity of related HAT MOF, as indicated by H4K16Ac, demonstrating specificity. The modeling and validation of the small molecule inhibitor TH1834 represents a first step towards developing additional specific, targeted inhibitors of Tip60 that may lead to further improvements in the treatment of breast cancer