Open Source Tools for Biological Image Analysis

Made to measure: An introduction to quantifying microscopy data in the life sciences

Images are at the core of most modern biological experiments and are used as a major source of quantitative information. Numerous algorithms are available to process images and make them more amenable to be measured. Yet the nature of the quantitative output that is useful for a given biological experiment is uniquely dependent upon the question being investigated. Here, we discuss the 3 main types of information that can be extracted from microscopy data: intensity, morphology, and object counts or categorical labels. For each, we describe where they come from, how they can be measured, and what may affect the relevance of these measurements in downstream data analysis. Acknowledging that what makes a measurement 'good' is ultimately down to the biological question being investigated, this review aims at providing readers with a toolkit to challenge how they quantify their own data and be critical of conclusions drawn from quantitative bioimage analysis experiments.

Application of unimodal probability distribution models for morphological phenotyping of budding yeast

Morphological phenotyping of the budding yeast Saccharomyces cerevisiae has helped to greatly clarify the functions of genes and increase our understanding of cellular functional networks. It is necessary to understand cell morphology and perform quantitative morphological analysis (QMA) but assigning precise values to morphological phenotypes has been challenging. We recently developed the Unimodal Morphological Data image analysis pipeline for this purpose. All true values can be estimated theoretically by applying an appropriate probability distribution if the distribution of experimental values follows a unimodal pattern. This reliable pipeline allows several downstream analyses, including detection of subtle morphological differences, selection of mutant strains with similar morphology, clustering based on morphology, and study of morphological diversity. In addition to basic research, morphological analyses of yeast cells can also be used in applied research to monitor breeding and fermentation processes and control the fermentation activity of yeast cells.

Quantitative Analysis of Whole-Mount Fluorescence-Stained Tumor Spheroids in Phenotypic Drug Screens

Three-dimensional cell cultures, such as spheroids or organoids, serve as important models for drug screening purposes. Optical tissue clearing (OTC) enhances the visualization of fluorescence stainings and enables in toto microscopy of 3D cell culture models. Furthermore, subsequent automated image analysis tools convert qualitative confocal image sets into quantitative data. In this chapter, we describe a detailed protocol for preparation of HT29 cancer spheroids, 3D in toto immunostaining, glycerol-based OTC, whole-mount imaging, and semi-automated downstream image processing and segmentation for nuclear image analysis using open-source software.

Recent Advances in High-Content Imaging and Analysis in iPSC-Based Modelling of Neurodegenerative Diseases

In the field of neurodegenerative pathologies, the platforms for disease modelling based on patient-derived induced pluripotent stem cells (iPSCs) represent a valuable molecular diagnostic/prognostic tool. Indeed, they paved the way for the in vitro recapitulation of the pathological mechanisms underlying neurodegeneration and for characterizing the molecular heterogeneity of disease manifestations, also enabling drug screening approaches for new therapeutic candidates. A major challenge is related to the choice and optimization of the morpho-functional study designs in human iPSC-derived neurons to deeply detail the cell phenotypes as markers of neurodegeneration. In recent years, the specific combination of high-throughput screening with subcellular resolution microscopy for cell-based high-content imaging (HCI) screening allowed in-depth analyses of cell morphology and neurite trafficking in iPSC-derived neuronal cells by using specific cutting-edge microscopes and automated computational assays. The present work aims to describe the main recent protocols and advances achieved with the HCI analysis in iPSC-based modelling of neurodegenerative diseases, highlighting technical and bioinformatics tips and tricks for further uses and research. To this end, microscopy requirements and the latest computational pipelines to analyze imaging data will be explored, while also providing an overview of the available open-source high-throughput automated platforms.

DisGUVery: A Versatile Open-Source Software for High-Throughput Image Analysis of Giant Unilamellar Vesicles

Giant unilamellar vesicles (GUVs) are cell-sized aqueous compartments enclosed by a phospholipid bilayer. Due to their cell-mimicking properties, GUVs have become a widespread experimental tool in synthetic biology to study membrane properties and cellular processes. In stark contrast to the experimental progress, quantitative analysis of GUV microscopy images has received much less attention. Currently, most analysis is performed either manually or with custom-made scripts, which makes analysis time-consuming and results difficult to compare across studies. To make quantitative GUV analysis accessible and fast, we present DisGUVery, an open-source, versatile software that encapsulates multiple algorithms for automated detection and analysis of GUVs in microscopy images. With a performance analysis, we demonstrate that DisGUVery's three vesicle detection modules successfully identify GUVs in images obtained with a wide range of imaging sources, in various typical GUV experiments. Multiple predefined analysis modules allow the user to extract properties such as membrane fluorescence, vesicle shape, and internal fluorescence from large populations. A new membrane segmentation algorithm facilitates spatial fluorescence analysis of nonspherical vesicles. Altogether, DisGUVery provides an accessible tool to enable high-throughput automated analysis of GUVs, and thereby to promote quantitative data analysis in synthetic cell research.

Dermal Penetration Analysis of Curcumin in an ex vivo Porcine Ear Model Using Epifluorescence Microscopy and Digital Image Processing

INTRODUCTION

Curcumin is a promising drug candidate, but its use for dermal application is limited due to its poor aqueous solubility. Thus, formulations that increase the solubility of curcumin are needed to fully exploit the therapeutic potential of curcumin. Various previous studies address this issue, but a comparison of the efficacy between these formulations remains difficult. The reason for this is a missing standard formulation as benchmark control and an easy-to-use skin penetration model that allows for a fast discrimination between different formulations.

OBJECTIVE

Thus, the aims of this study were the development of a curcumin standard formulation and a screening tool that allows for a fast discrimination between the dermal penetration efficacies of curcumin from different formulations.

METHODS

Ethanolic curcumin solutions were selected as simple and easy to produce standard formulations, and the ex vivo porcine ear model, coupled with epifluorescence microscopy and subsequent digital image analysis, was utilized to determine the dermal penetration efficacy of curcumin from the different formulations.

RESULTS

Results show that the utilized skin penetration model is a suitable and versatile tool that enables not only a fast determination of the dermal penetration efficacy of curcumin from different formulations but also a detailed and mechanistic information on the fate of chemical compounds after dermal penetration. Ethanolic solutions containing 0.25% curcumin were found to be the most suitable standard formulation.

CONCLUSIONS

Results of the study provide a new, effective screening tool for the development of dermal formulations for improved dermal delivery of curcumin.

The ImageJ ecosystem: Open-source software for image visualization, processing, and analysis

For decades, biologists have relied on software to visualize and interpret imaging data. As techniques for acquiring images increase in complexity, resulting in larger multidimensional datasets, imaging software must adapt. ImageJ is an open-source image analysis software platform that has aided researchers with a variety of image analysis applications, driven mainly by engaged and collaborative user and developer communities. The close collaboration between programmers and users has resulted in adaptations to accommodate new challenges in image analysis that address the needs of ImageJ's diverse user base. ImageJ consists of many components, some relevant primarily for developers and a vast collection of user-centric plugins. It is available in many forms, including the widely used Fiji distribution. We refer to this entire ImageJ codebase and community as the ImageJ ecosystem. Here we review the core features of this ecosystem and highlight how ImageJ has responded to imaging technology advancements with new plugins and tools in recent years. These plugins and tools have been developed to address user needs in several areas such as visualization, segmentation, and tracking of biological entities in large, complex datasets. Moreover, new capabilities for deep learning are being added to ImageJ, reflecting a shift in the bioimage analysis community towards exploiting artificial intelligence. These new tools have been facilitated by profound architectural changes to the ImageJ core brought about by the ImageJ2 project. Therefore, we also discuss the contributions of ImageJ2 to enhancing multidimensional image processing and interoperability in the ImageJ ecosystem.

Hair Follicle Targeting and Dermal Drug Delivery with Curcumin Drug Nanocrystals-Essential Influence of Excipients

Many active pharmaceutical ingredients (API) possess poor aqueous solubility and thus lead to poor bioavailability upon oral administration and topical application. Nanocrystals have a well-established, universal formulation approach to overcome poor solubility. Various nanocrystal-based products have entered the market for oral application. However, their use in dermal formulations is relatively novel. Previous studies confirmed that nanocrystals are a superior formulation principle to improve the dermal penetration of poorly soluble API. Other studies showed that nanocrystals can also be used to target the hair follicles where they create a drug depot, enabling long acting drug therapy with only one application. Very recent studies show that also the vehicle in which the nanocrystals are incorporated can have a tremendous influence on the pathway of the API and the nanocrystals. In order to elucidate the influence of the excipient in more detail, a systematic study was conducted to investigate the influence of excipients on the penetration efficacy of the formulated API and the pathway of nanocrystals upon dermal application. Results showed that already small quantities of excipients can strongly affect the passive dermal penetration of curcumin and the hair follicle targeting of curcumin nanocrystals. The addition of 2% ethanol promoted hair follicle targeting of nanocrystals and hampered passive diffusion into the stratum corneum of the API, whereas the addition of glycerol hampered hair follicle targeting and promoted passive diffusion. Propylene glycol was found to promote both pathways. In fact, the study proved that formulating nanocrystals to improve the bioefficacy of poorly soluble API upon dermal application is highly effective. However, this is only true, if the correct excipient is selected for the formulation of the vehicle. The study also showed that excipients can be used to allow for a targeted dermal drug delivery, which enables to control if API should be delivered via passive diffusion and/or as drug reservoir by depositing API in the hair follicles.

Hair follicle targeting with curcumin nanocrystals: Influence of the formulation properties on the penetration efficacy

Nanocrystals are a universal formulation approach for improved drug delivery of poorly water-soluble drug substances. Besides oral application, also topical application of the nanocrystals is feasible, because the increased kinetic solubility of the nanocrystals results in an increased concentration gradient, thus fostering passive, dermal penetration. Nanocrystals are also promising for targeting drug substances into the hair follicle. After penetration into the hair follicle, the nanocrystals could form a depot from which the active is released into the hair follicle. Thus, leading to a long-lasting and very efficient dermal drug delivery. The efficacy of nanocrystals to penetrate the hair follicles and the influence of the vehicle in which the nanocrystals are suspended was not yet investigated. Therefore, in this study curcumin nanocrystals with a size of about 300 nm were produced and incorporated into gels with different properties. The efficacy to penetrate the hair follicles, as well as the passive, dermal penetration, was assessed on the ex-vivo pig ear model. Nanocrystals were efficiently taken up by the hair follicles and reached the lower part of the infundibulum. This region is optimal for efficient drug delivery because the barrier of the lower infundibulum is not fully developed and thus more permeable, which results in a less hindered passive diffusion of drug substances. The penetration efficacy of the nanocrystals into the hair follicles was not affected by the different types of vehicles, which represented either oleogels or hydrogels that varied in viscosity as well as in the type and the concentration of the gelling agent. All gels possessed a shear-thinning flow behavior and it is hypothesized that all gels fluidized during the skin massage, whereby leading to similarly low viscosities than the aqueous nanosuspension and thus to similar penetration results. The passive, dermal penetration of curcumin was different for the different gels and the main driving parameter leading to good passive diffusion was caused by good skin hydrating properties of the vehicle. The best passive penetration was achieved from hydrogels that contained a humectant. However, the addition of the humectant reduced the efficacy of the nanocrystals to penetrate the hair follicle. Data so far, therefore, suggest that hair follicle targeting with nanocrystals that are suspended in water or simple, shear-thinning gels is highly effective. However, the addition of other excipients, e.g. humectants, to these vehicles might cause changes in the penetration profiles. More research in this regard is needed to understand these observations in more detail.

Intravital imaging of megakaryocytes

The dynamics of platelet formation could only be investigated since the development of two-photon microscopy in combination with suitable fluorescent labeling strategies. In this review paper, we give an overview of recent advances in fluorescence imaging of the bone marrow that have contributed to our understanding of platelet biogenesis during the last decade. We make a brief survey through the perspectives and limitations of today's intravital imaging, but also discuss complementary methods that may help to piece together the puzzle of megakaryopoiesis and platelet formation.