Assessing the Phase Separation Propensity of Proteins in Living Cells Through Optodroplet Formation

Phase separation is emerging as a key mechanism to describe the formation of membraneless organelles in the cell. It depends on the multivalent (self-) interaction properties of the macromolecules involved and can be observed in aqueous solutions under controlled conditions in vitro with purified components. However, to experimentally demonstrate that this process indeed occurs in the complex environment of living cells remains difficult. Here, we describe an assay based on light-induced association of proteins into complexes termed optodroplets that are in the hundred nm to μm size range. The formation and dissociation of these optodroplets can be followed over time in living cells by fluorescence microscopy to evaluate the propensity of proteins to demix and to form phase-separated subcompartments. The optodroplet assay is based on the fusion of a protein of interest with the photolyase homology region (PHR) protein domain from Arabidopsis thaliana, which can undergo reversible homo-oligomerization upon illumination with blue light. Using this approach, candidate proteins and their interaction-deficient or interaction-enhanced variants can be compared to each other or to reference proteins with known phase separation features. By quantifying the resulting microscopy images, the propensity of a given protein construct to assemble into a phase-separated subcompartment can be assessed.

Microscopy-Based Multiwell Assay to Characterize Disturbed Bacterial Morphogenesis Upon Antibiotic Action

The urgent need of new antimicrobial agents to combat life-threatening bacterial infections demands the identification and characterization of novel compounds that interfere with new and unprecedented target pathways or structures in multiresistant bacteria. Here, bacterial cell division has emerged as a new and promising target pathway for antibiotic intervention. Compounds, which inhibit division, commonly induce a characteristic filamentation phenotype of rod-shaped bacteria, such as Bacillus subtilis. Hence, this filamentation phenotype can be used to identify and characterize novel compounds that primarily target bacterial cell division. Since novel compounds of both synthetic and natural product origin are often available in small amounts only, thereby limiting the number of assays during mode of action studies, we here describe a semiautomated, microscopy-based approach that requires only small volumes of compounds to allow for the real-time observation of their effects on living bacteria, such as filamentation or cell lysis, in high-throughput 96-well-based formats. We provide a detailed workflow for the initial characterization of multiple compounds at once and further tools for the initial, microscopy-based characterization of their antibacterial mode of action.

Machine-assisted interpretation of auramine stains substantially increases through-put and sensitivity of microscopic tuberculosis diagnosis

Of all bacterial infectious diseases, infection by Mycobacterium tuberculosis poses one of the highest morbidity and mortality burdens on humans throughout the world. Due to its speed and cost-efficiency, manual microscopy of auramine-stained sputum smears remains a crucial first-line detection method. However, it puts considerable workload on laboratory staff and suffers from a limited sensitivity. Here we validate a scanning and analysis system that combines fully-automated microscopy with deep-learning based image analysis. After automated scanning, the system summarizes diagnosis-relevant image information and presents it to the microbiologist in order to assist diagnosis. We tested the benefit of the automated scanning and analysis system using 531 slides from routine workflow, of which 56 were from culture positive specimen. Assistance by the scanning and analysis system allowed for a higher sensitivity (40/56 positive slides detected) than manual microscopy (34/56 positive slides detected), while greatly reducing manual slide-analysis time from a recommended 5-15 min to around 10 s per slide on average.

Design and implementation of a low cost, modular, adaptable and open-source XYZ positioning system for neurophysiology

In recent years, open-source 3D printing technologies have become increasingly applied to biological research. We have created a fully open-source, versatile and low cost XYZ positioning system using 3D printer components. As this system is controlled by a Python3 based operating system running on a Raspberry Pi 3 Model B, its behaviour can be adapted to meet multiple needs in neurophysiology. We have developed two main applications of this system. First, we have created an automated microscopy script that links seamlessly with image stitching plugins in ImageJ (Fiji) allowing the user to create high resolution montages. Second, we have created a series of movement scripts allowing the application of graded rates of stretch to muscle spindles. Here we outline the construction and implementation of this system and discuss how we have utilised this tool in our research.

Light-Induced Transcription Activation for Time-Lapse Microscopy Experiments in Living Cells

Gene expression can be monitored in living cells via the binding of fluorescently tagged proteins to RNA repeats engineered into a reporter transcript. This approach makes it possible to trace temporal changes of RNA production in real time in living cells to dissect transcription regulation. For a mechanistic analysis of the underlying activation process, it is essential to induce gene expression with high accuracy. Here, we describe how this can be accomplished with an optogenetic approach termed blue light-induced chromatin recruitment (BLInCR). It employs the recruitment of an activator protein to a target promoter via the interaction between the PHR and CIBN plant protein domains. This process occurs within seconds after setting the light trigger and is reversible. Protocols for continuous activation as well as pulsed activation and reactivation with imaging either by laser scanning confocal microscopy or automated widefield microscopy are provided. For the semiautomated quantification of the resulting image series, an approach has been implemented in a set of scripts in the R programming language. Thus, the complete workflow of the BLInCR method is described for mechanistic studies of the transcription activation process as well as the persistence and memory of the activated state.

Progress in Automated Urinalysis

New technological advances have paved the way for significant progress in automated urinalysis. Quantitative reading of urinary test strips using reflectometry has become possible, while complementary metal oxide semiconductor (CMOS) technology has enhanced analytical sensitivity and shown promise in microalbuminuria testing. Microscopy-based urine particle analysis has greatly progressed over the past decades, enabling high throughput in clinical laboratories. Urinary flow cytometry is an alternative for automated microscopy, and more thorough analysis of flow cytometric data has enabled rapid differentiation of urinary microorganisms. Integration of dilution parameters (e.g., creatinine, specific gravity, and conductivity) in urine test strip readers and urine particle flow cytometers enables correction for urinary dilution, which improves result interpretation. Automated urinalysis can be used for urinary tract screening and for diagnosing and monitoring a broad variety of nephrological and urological conditions; newer applications show promising results for early detection of urothelial cancer. Concomitantly, the introduction of matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) has enabled fast identification of urinary pathogens. Automation and workflow simplification have led to mechanical integration of test strip readers and particle analysis in urinalysis. As the information obtained by urinalysis is complex, the introduction of expert systems may further reduce analytical errors and improve the quality of sediment and test strip analysis. With the introduction of laboratory-on-a-chip approaches and the use of microfluidics, new affordable applications for quantitative urinalysis and readout on cell phones may become available. In this review, we present the main recent developments in automated urinalysis and future perspectives.

Microfluidic Transfection for High-Throughput Mammalian Protein Expression

Mammalian synthetic biology and cell biology would greatly benefit from improved methods for highly parallel transfection, culturing, and interrogation of mammalian cells. Transfection is routinely performed on high-throughput microarrays, but this setup requires manual cell culturing and precludes precise control over the cell environment. As an alternative, microfluidic transfection devices streamline cell loading and culturing. Up to 280 transfections can be implemented on the chip at high efficiency. The culturing environment is tightly regulated and chambers physically separate the transfection reactions, preventing cross-contamination. Unlike typical biological assays that rely on end-point measurements, the microfluidic chip can be integrated with high-content imaging, enabling the evaluation of cellular behavior and protein expression dynamics over time.

An automated epifluorescence microscopy imaging assay for the identification of phospho-AKT level modulators in breast cancer cells

AKT is an enzyme of the PI3K/pAKT pathway, regulating proliferation and cell survival. High basal levels of active, phosphorylated AKT (pAKT) are associated with tumor progression and therapeutic resistance in some breast cancer subtypes, including HER2 positive breast cancers. Various stimuli can increase pAKT levels and elevated basal pAKT levels are a feature of PTEN-deficient breast cancer cell lines. The aim of this study was to develop an assay able to identify modulators of pAKT levels using an automated epifluorescence microscope and high content analysis. To develop this assay, we used HCC-1569, a PTEN-deficient, HER2-overexpressing breast cancer cell line with elevated basal pAKT levels. HCC-1569 cells were treated with a selective pharmacological inhibitor of AKT (MK-2206) to reduce basal pAKT levels or EGF to increase pAKT levels. Immunofluorescence images were acquired using an automated epifluorescence microscope and integrated intensity of cytoplasmic pAKT staining was calculated using high content analysis software. Mean and median integrated cytoplasmic intensity were normalized using fold change and standard score to assess assay quality and to identify most robust data analysis. The highest z' factor was achieved for median data normalization using the standard score method (z' = 0.45). Using our developed assay we identified the calcium homeostasis regulating proteins TPRV6, STIM1 and TRPC1 as modulators of pAKT levels in HCC-1569 cells. Calcium signaling controls a diverse array of cellular processes and some calcium homeostasis regulating proteins are involved in modulating pAKT levels in cancer cells. Thus, these identified hits present promising targets for further assessment.

The Ancient Genetic Networks of Obesity: Whole-Animal Automated Screening for Conserved Fat Regulators

Caenorhabditis elegans is the first and only metazoan model that enables whole-body gene knockdown by simply feeding their standard laboratory diet, E. coli, carrying RNA interference (RNAi)-expressing constructs. The simplicity of the RNAi treatment, small size, and fast reproduction rate of C. elegans allow us to perform whole-animal high-throughput genetic screens in wild-type, mutant, or otherwise genetically modified C. elegans. In addition, more than 65% of C. elegans genes are conserved in mammals including human. In particular, C. elegans metabolic pathways are highly conserved, which supports the study of complex diseases such as obesity in this genetically tractable model system. In this chapter, we present a detailed protocol for automated high-throughput whole-animal RNAi screening to identify the pathways promoting obesity in diet-induced and genetically driven obese C. elegans. We describe an optimized high-content screening protocol to score fat mass and body fat distribution in whole animals at large scale. We provide optimized pipelines to automatically score phenotypes using the open-source CellProfiler platform within the context of supercomputer clusters. Further, we present a guideline to optimize information workflow from the automated microscope to a searchable database. The approaches described here enable unveiling the whole network of gene-gene and gene-environment interactions that define metabolic health or disease status in this proven model of human disease, but similar principles can be applied to other disease models.

Quantitative 3D-imaging for cell biology and ecology of environmental microbial eukaryotes

We present a 3D-fluorescence imaging and classification tool for high throughput analysis of microbial eukaryotes in environmental samples. It entails high-content feature extraction that permits accurate automated taxonomic classification and quantitative data about organism ultrastructures and interactions. Using plankton samples from the Tara Oceans expeditions, we validate its applicability to taxonomic profiling and ecosystem analyses, and discuss its potential for future integration of eukaryotic cell biology into evolutionary and ecological studies.

Quantitative 3D-imaging for cell biology and ecology of environmental microbial eukaryotes

We present a 3D-fluorescence imaging and classification tool for high throughput analysis of microbial eukaryotes in environmental samples. It entails high-content feature extraction that permits accurate automated taxonomic classification and quantitative data about organism ultrastructures and interactions. Using plankton samples from the Tara Oceans expeditions, we validate its applicability to taxonomic profiling and ecosystem analyses, and discuss its potential for future integration of eukaryotic cell biology into evolutionary and ecological studies.

Our planet’s ecosystems – from its oceans to its forests – are teeming with microbes. DNA analysis of environmental samples shows that many of these microbes belong to a group known as protists. This group consists of single-celled organisms that are close relatives of fungi, plants and animals. Though protists are a widespread and diverse group, scientists know little about them. One reason for this is the lack of high-throughput ways to recognize and count protists in environmental samples.

Colin, Coelho et al. set out to tackle this blind spot in ecology and cell biology by developing an automated imaging system. The system needed to image many kinds of protist cells in enough detail to see the features inside. The end-result was a 3D-imaging technique called e-HCFM – which is short for “environmental high content fluorescence microscopy”. Colin, Coelho et al. went on to use the technique on 72 samples collected on an expedition across the world’s oceans. This allowed them to automatically image, recognize and classify over 330,000 organisms.

This approach and new dataset will benefit researchers working in many fields, from cell biology to ecology, computational biology and beyond. In the future, this imaging method might integrate with techniques that can analyze the DNA in individual cells. This would allow scientists to link protists’ visible features to their genetic information, in a way that will scale from single cells up to entire ecosystems.

A quantitative FastFUCCI assay defines cell cycle dynamics at a single-cell level

The fluorescence ubiquitination-based cell cycle indicator (FUCCI) is a powerful tool for use in live cells but current FUCCI-based assays have limited throughput in terms of image processing and quantification. Here, we developed a lentiviral system that rapidly introduced FUCCI transgenes into cells by using an all-in-one expression cassette, FastFUCCI. The approach alleviated the need for sequential transduction and characterisation, improving labelling efficiency. We coupled the system to an automated imaging workflow capable of handling large datasets. The integrated assay enabled analyses of single-cell readouts at high spatiotemporal resolution. With the assay, we captured in detail the cell cycle alterations induced by antimitotic agents. We found that treated cells accumulated at G2 or M phase but eventually advanced through mitosis into the next interphase, where the majority of cell death occurred, irrespective of the preceding mitotic phenotype. Some cells appeared viable after mitotic slippage, and a fraction of them subsequently re-entered S phase. Accordingly, we found evidence that targeting the DNA replication origin activity sensitised cells to paclitaxel. In summary, we demonstrate the utility of the FastFUCCI assay for quantifying spatiotemporal dynamics and identify its potential in preclinical drug development.

High throughput physiological screening of iPSC-derived cardiomyocytes for drug development

Cardiac drug discovery is hampered by the reliance on non-human animal and cellular models with inadequate throughput and physiological fidelity to accurately identify new targets and test novel therapeutic strategies. Similarly, adverse drug effects on the heart are challenging to model, contributing to costly failure of drugs during development and even after market launch. Human induced pluripotent stem cell derived cardiac tissue represents a potentially powerful means to model aspects of heart physiology relevant to disease and adverse drug effects, providing both the human context and throughput needed to improve the efficiency of drug development. Here we review emerging technologies for high throughput measurements of cardiomyocyte physiology, and comment on the promises and challenges of using iPSC-derived cardiomyocytes to model disease and introduce the human context into early stages of drug discovery. This article is part of a Special Issue entitled: Cardiomyocyte biology: Integration of Developmental and Environmental Cues in the Heart edited by Marcus Schaub and Hughes Abriel.

High Content Imaging of Early Morphological Signatures Predicts Long Term Mineralization Capacity of Human Mesenchymal Stem Cells upon Osteogenic Induction

Human bone marrow-derived multipotent mesenchymal stromal cells, often referred to as mesenchymal stem cells (MSCs), represent an attractive cell source for many regenerative medicine applications due to their potential for multi-lineage differentiation, immunomodulation, and paracrine factor secretion. A major complication for current MSC-based therapies is the lack of well-defined characterization methods that can robustly predict how they will perform in a particular in vitro or in vivo setting. Significant advances have been made with identifying molecular markers of MSC quality and potency using multivariate genomic and proteomic approaches, and more recently with advanced techniques incorporating high content imaging to assess high-dimensional single cell morphological data. We sought to expand upon current methods of high dimensional morphological analysis by investigating whether short term cell and nuclear morphological profiles of MSCs from multiple donors (at multiple passages) correlated with long term mineralization upon osteogenic induction. Using the combined power of automated high content imaging followed by automated image analysis, we demonstrated that MSC morphology after 3 days was highly correlated with 35 day mineralization and comparable to other methods of MSC osteogenesis assessment (such as alkaline phosphatase activity). We then expanded on this initial morphological characterization and identified morphological features that were highly predictive of mineralization capacities (>90% accuracy) of MSCs from additional donors and different manufacturing techniques using linear discriminant analysis. Together, this work thoroughly demonstrates the predictive power of MSC morphology for mineralization capacity and motivates further studies into MSC morphology as a predictive marker for additional in vitro and in vivo responses.

Application of Imaging-Based Assays in Microplate Formats for High-Content Screening

The use of multiparametric microscopy-based screens with automated analysis has enabled the large-scale study of biological phenomena that are currently not measurable by any other method. Collectively referred to as high-content screening (HCS), or high-content analysis (HCA), these methods rely on an expanding array of imaging hardware and software automation. Coupled with an ever-growing amount of diverse chemical matter and functional genomic tools, HCS has helped open the door to a new frontier of understanding cell biology through phenotype-driven screening. With the ability to interrogate biology on a cell-by-cell basis in highly parallel microplate-based platforms, the utility of HCS continues to grow as advancements are made in acquisition speed, model system complexity, data management, and analysis systems. This chapter uses an example of screening for genetic factors regulating mitochondrial quality control to exemplify the practical considerations in developing and executing high-content campaigns.

21(st) century workflow: A proposal

Digital pathology is rapidly developing, but early systems have been slow to gain traction outside of niche applications such as: Second-opinion telepathology, immunostain interpretation, and intraoperative telepathology. Pathologists have not yet developed a well-articulated plan for effectively utilizing digital imaging technology in their work. This paper outlines a proposal that is intended to begin meaningful progress toward achieving helpful computer-assisted pathology sign-out systems, such as pathologists' computer-assisted diagnosis (pCAD). pCAD is presented as a hypothetical intelligent computer system that would integrate advanced image analysis and better utilization of existing digital pathology data from lab information systems. A detailed example of automated digital pathology is presented, as an automated breast cancer lymph node sign-out. This proposal provides stakeholders with a conceptual framework that can be used to facilitate development work, communication, and identification of new automation strategies.