The potential of high-content high-throughput microscopy in drug discovery

Fourier Ptychographic Microscopy 10 Years on: A Review

Fourier ptychographic microscopy (FPM) emerged as a prominent imaging technique in 2013, attracting significant interest due to its remarkable features such as precise phase retrieval, expansive field of view (FOV), and superior resolution. Over the past decade, FPM has become an essential tool in microscopy, with applications in metrology, scientific research, biomedicine, and inspection. This achievement arises from its ability to effectively address the persistent challenge of achieving a trade-off between FOV and resolution in imaging systems. It has a wide range of applications, including label-free imaging, drug screening, and digital pathology. In this comprehensive review, we present a concise overview of the fundamental principles of FPM and compare it with similar imaging techniques. In addition, we present a study on achieving colorization of restored photographs and enhancing the speed of FPM. Subsequently, we showcase several FPM applications utilizing the previously described technologies, with a specific focus on digital pathology, drug screening, and three-dimensional imaging. We thoroughly examine the benefits and challenges associated with integrating deep learning and FPM. To summarize, we express our own viewpoints on the technological progress of FPM and explore prospective avenues for its future developments.

Volumetric imaging of human mesenchymal stem cells (hMSCs) for non-destructive quantification of 3D cell culture growth

The adoption of cell-based therapies into the clinic will require tremendous large-scale expansion to satisfy future demand, and bioreactor-microcarrier cultures are best suited to meet this challenge. The use of spherical microcarriers, however, precludes in-process visualization and monitoring of cell number, morphology, and culture health. The development of novel expansion methods also motivates the advancement of analytical methods used to characterize these microcarrier cultures. A robust optical imaging and image-analysis assay to non-destructively quantify cell number and cell volume was developed. This method preserves 3D cell morphology and does not require membrane lysing, cellular detachment, or exogenous labeling. Complex cellular networks formed in microcarrier aggregates were imaged and analyzed in toto. Direct cell enumeration of large aggregates was performed in toto for the first time. This assay was successfully applied to monitor cellular growth of mesenchymal stem cells attached to spherical hydrogel microcarriers over time. Elastic scattering and fluorescence lightsheet microscopy were used to quantify cell volume and cell number at varying spatial scales. The presented study motivates the development of on-line optical imaging and image analysis systems for robust, automated, and non-destructive monitoring of bioreactor-microcarrier cell cultures.

Correlative Multi-Modal Microscopy: A Novel Pipeline for Optimizing Fluorescence Microscopy Resolutions in Biological Applications

The modern fluorescence microscope is the convergence point of technologies with different performances in terms of statistical sampling, number of simultaneously analyzed signals, and spatial resolution. However, the best results are usually obtained by maximizing only one of these parameters and finding a compromise for the others, a limitation that can become particularly significant when applied to cell biology and that can reduce the spreading of novel optical microscopy tools among research laboratories. Super resolution microscopy and, in particular, molecular localization-based approaches provide a spatial resolution and a molecular localization precision able to explore the scale of macromolecular complexes in situ. However, its use is limited to restricted regions, and consequently few cells, and frequently no more than one or two parameters. Correlative microscopy, obtained by the fusion of different optical technologies, can consequently surpass this barrier by merging results from different spatial scales. We discuss here the use of an acquisition and analysis correlative microscopy pipeline to obtain high statistical sampling, high content, and maximum spatial resolution by combining widefield, confocal, and molecular localization microscopy.

Generalising from conventional pipelines using deep learning in high-throughput screening workflows

The study of complex diseases relies on large amounts of data to build models toward precision medicine. Such data acquisition is feasible in the context of high-throughput screening, in which the quality of the results relies on the accuracy of the image analysis. Although state-of-the-art solutions for image segmentation employ deep learning approaches, the high cost of manually generating ground truth labels for model training hampers the day-to-day application in experimental laboratories. Alternatively, traditional computer vision-based solutions do not need expensive labels for their implementation. Our work combines both approaches by training a deep learning network using weak training labels automatically generated with conventional computer vision methods. Our network surpasses the conventional segmentation quality by generalising beyond noisy labels, providing a 25% increase of mean intersection over union, and simultaneously reducing the development and inference times. Our solution was embedded into an easy-to-use graphical user interface that allows researchers to assess the predictions and correct potential inaccuracies with minimal human input. To demonstrate the feasibility of training a deep learning solution on a large dataset of noisy labels automatically generated by a conventional pipeline, we compared our solution against the common approach of training a model from a small manually curated dataset by several experts. Our work suggests that humans perform better in context interpretation, such as error assessment, while computers outperform in pixel-by-pixel fine segmentation. Such pipelines are illustrated with a case study on image segmentation for autophagy events. This work aims for better translation of new technologies to real-world settings in microscopy-image analysis.

Learning the rules of collective cell migration using deep attention networks

Collective, coordinated cellular motions underpin key processes in all multicellular organisms, yet it has been difficult to simultaneously express the ‘rules’ behind these motions in clear, interpretable forms that effectively capture high-dimensional cell-cell interaction dynamics in a manner that is intuitive to the researcher. Here we apply deep attention networks to analyze several canonical living tissues systems and present the underlying collective migration rules for each tissue type using only cell migration trajectory data. We use these networks to learn the behaviors of key tissue types with distinct collective behaviors—epithelial, endothelial, and metastatic breast cancer cells—and show how the results complement traditional biophysical approaches. In particular, we present attention maps indicating the relative influence of neighboring cells to the learned turning decisions of a ‘focal cell’–the primary cell of interest in a collective setting. Colloquially, we refer to this learned relative influence as ‘attention’, as it serves as a proxy for the physical parameters modifying the focal cell’s future motion as a function of each neighbor cell. These attention networks reveal distinct patterns of influence and attention unique to each model tissue. Endothelial cells exhibit tightly focused attention on their immediate forward-most neighbors, while cells in more expansile epithelial tissues are more broadly influenced by neighbors in a relatively large forward sector. Attention maps of ensembles of more mesenchymal, metastatic cells reveal completely symmetric attention patterns, indicating the lack of any particular coordination or direction of interest. Moreover, we show how attention networks are capable of detecting and learning how these rules change based on biophysical context, such as location within the tissue and cellular crowding. That these results require only cellular trajectories and no modeling assumptions highlights the potential of attention networks for providing further biological insights into complex cellular systems.

Collective behaviors are crucial to the function of multicellular life, with large-scale, coordinated cell migration enabling processes spanning organ formation to coordinated skin healing. However, we lack effective tools to discover and cleanly express collective rules at the level of an individual cell. Here, we employ a carefully structured neural network to extract collective information directly from cell trajectory data. The network is trained on data from various systems, including canonical collective cell systems (HUVEC and MDCK cells) which display visually distinct forms of collective motion, and metastatic cancer cells (MDA-MB-231) which are highly uncoordinated. Using these trained networks, we can produce attention maps for each system, which indicate how a cell within a tissue takes in information from its surrounding neighbors, as a function of weights assigned to those neighbors. Thus for a cell type in which cells tend to follow the path of the cell in front, the attention maps will display high weights for cells spatially forward of the focal cell. We present results in terms of additional metrics, such as accuracy plots and number of interacting cells, and encourage future development of improved metrics.

Monitoring cell endocytosis of liposomes by real-time electrical impedance spectroscopy

Evaluation and understanding the effect of drug delivery in in vitro systems is fundamental in drug discovery. We present an assay based on real-time electrical impedance spectroscopy (EIS) measurements that can be used to follow the internalisation and cytotoxic effect of a matrix metalloproteinase (MMP)-sensitive liposome formulation loaded with oxaliplatin (OxPt) on colorectal cancer cells. The EIS response identified two different cellular processes: (i) a negative peak in the cell index (CI) within the first 5 h, due to onset of liposome endocytosis, followed by (ii) a subsequent CI increase, due to the reattachment of cells until the onset of cytotoxicity with a decrease in CI. Free OxPt or OxPt-loaded Stealth liposomes did not show this two-stage EIS response; the latter can be due to the fact that Stealth cannot be cleaved by MMPs and thus is not taken up by the cells. Real-time bright-field imaging supported the EIS data, showing variations in cell adherence and cell morphology after exposure to the different liposome formulations. A drastic decrease in cell coverage as well as rounding up of cells during the first 5 h of exposure to OxPt-loaded (MMP)-sensitive liposome formulation is reflected by the first negative EIS response, which indicates the onset of liposome endocytosis. Graphical abstract.

Quantitative analysis of interactive behavior of mitochondria and lysosomes using structured illumination microscopy

Super-resolution optical microscopy has extended the spatial resolution of cell biology from the cellular level to the nanoscale, enabling the observation of the interactive behavior of single mitochondria and lysosomes. Quantitative parametrization of interactions between mitochondria and lysosomes under super-resolution optical microscopy, however, is currently unavailable, which has severely limited our understanding of the molecular machinery underlying mitochondrial functionality. Here, we introduce an M-value to quantitatively investigate mitochondria and lysosome contact (MLC) and mitophagy under structured illumination microscopy. We found that the M-value for an MLC is typically less than 0.4, whereas in mitophagy it ranges from 0.5 to 1.0. This system permits further investigation of the detailed molecular mechanism governing the interactive behavior of mitochondria and lysosomes.

HCS Methodology for Helping in Lab Scale Image-Based Assays

High-content screening (HCS) automates image acquisition and analysis in microscopy. This technology considers the multiple parameters contained in the images and produces statistically significant results. The recent improvements in image acquisition throughput, image analysis, and machine learning (ML) have popularized this kind of experiments, emphasizing the need for new tools and know-how to help in its design, analysis, and data interpretation. This chapter summarizes HCS recommendations for lab scale assays and provides both macros for HCS-oriented image analysis and user-friendly tools for data mining processes. All the steps described herein are oriented to a wide variety of image cell-based experiments. The workflows are illustrated with practical examples and test images. Their use is expected to help analyze thousands of images, create graphical representations, and apply machine learning models on HCS.

Speckle-structured illumination for 3D phase and fluorescence computational microscopy

High-content biological microscopy targets high-resolution imaging across large fields-of-view, often achieved by computational imaging approaches. Previously, we demonstrated 2D multimodal high-content microscopy via structured illumination microscopy (SIM) with resolution > 2 × the diffraction limit, using speckle illumination from Scotch tape. In this work, we extend the method to 3D by leveraging the fact that the speckle illumination is in fact a 3D structured pattern. We use both a coherent and an incoherent imaging model to develop algorithms for joint retrieval of the 3D super-resolved fluorescent and complex-field distributions of the sample. Our reconstructed images resolve features beyond the physical diffraction-limit set by the system's objective and demonstrate 3D multimodal imaging with ∼ 0.6 × 0.6 × 6   μ m3 resolution over a volume of ∼ 314 × 500 × 24   μ m3.

Computational structured illumination for high-content fluorescence and phase microscopy

High-content biological microscopy targets high-resolution imaging across large fields-of-view (FOVs). Recent works have demonstrated that computational imaging can provide efficient solutions for high-content microscopy. Here, we use speckle structured illumination microscopy (SIM) as a robust and cost-effective solution for high-content fluorescence microscopy with simultaneous high-content quantitative phase (QP). This multi-modal compatibility is essential for studies requiring cross-correlative biological analysis. Our method uses laterally-translated Scotch tape to generate high-resolution speckle illumination patterns across a large FOV. Custom optimization algorithms then jointly reconstruct the sample's super-resolution fluorescent (incoherent) and QP (coherent) distributions, while digitally correcting for system imperfections such as unknown speckle illumination patterns, system aberrations and pattern translations. Beyond previous linear SIM works, we achieve resolution gains of 4× the objective's diffraction-limited native resolution, resulting in 700 nm fluorescence and 1.2 μm QP resolution, across a FOV of 2 × 2.7 mm 2 , giving a space-bandwidth product (SBP) of 60 megapixels.

Wide-field anti-aliased quantitative differential phase contrast microscopy

Differential phase contrast (DPC) microscopy is a popular methodology to recover quantitative phase information of thin transparent samples under multi-axis asymmetric illumination patterns. Based on spatially partially coherent illuminations, DPC provides high-quality, speckle-free 3D reconstructions with lateral resolution up to twice the coherent diffraction limit, under the precondition that the pixel size of the imaging sensor is small enough to prevent spatial aliasing/undersampling. However, microscope cameras are in general designed to have a large pixel size so that the intensity information transmitted by the optical system cannot be adequately sampled or digitized. On the other hand, using an image sensor with a smaller pixel size or adding a magnification camera adapter to the camera can resolve the undersampling at the expense of a reduced field of view (FOV). To solve this tradeoff, we introduce a new variation of quantitative DPC approach, termed anti-aliased DPC (AADPC), which uses several aliased intensity images under asymmetric illuminations to recover wide-field aliasing-free phase images. Besides, phase transfer functions under different illumination patterns in DPC are analyzed to design an illumination scheme with better phase transfer characteristics. AADPC starts from an initial phase estimate obtained by a DPC-like deconvolution based on the system's weak phase transfer function under discrete half-annular illumination. Then the obtained initial phase map is further refined by the iterative de-multiplexing algorithm to overcome pixel-aliasing and improve the imaging resolution. The data redundancy requirement as well as the optimal illumination scheme of AADPC are analyzed and discussed based on several simulations, suggesting that the spatial undersampling can be mitigated through the iterative algorithm that uses only 4 images, yielding a nearly 4-fold increase in the space-bandwidth product (SBP) compared to the conventional DPC approach. We experimentally verify that AADPC can achieve a half-pitch imaging resolution of 345 nm, corresponding to 1.88× of the theoretical Nyquist-Shannon sampling resolution limit imposed by the sensor pixel size. The high-speed, high-throughput quantitative phase imaging capabilities of AADPC are also demonstrated by imaging HeLa cells mitosis in vitro, achieving a full-pitch lateral resolution of 665 nm across a wide FOV of 1.77mm² at 25 fps.

Synthetic 10FN3-based mono- and bivalent inhibitors of MDM2/X function

Engineered non-antibody scaffold proteins constitute a rapidly growing technology for diagnostics and modulation/perturbation of protein function. Here, we describe the rapid and systematic development of high-affinity 10FN3 domain inhibitors of the MDM2 and MDMX proteins. These are often overexpressed in cancer and represent attractive drug targets. Using facile in vitro expression and pull-down assay methodology, numerous design iterations addressing insertion site(s) and spacer length were screened for optimal presentation of an MDM2/X dual peptide inhibitor in the 10FN3 scaffold. Lead inhibitors demonstrated robust, on-target cellular inhibition of MDM2/X leading to activation of the p53 tumor suppressor. Significant improvement to target engagement was observed by increasing valency within a single 10FN3 domain, which has not been demonstrated previously. We further established stable reporter cell lines with tunable expression of EGFP-fused 10FN3 domain inhibitors, and showed their intracellular location to be contingent on target engagement. Importantly, competitive inhibition of MDM2/X by small molecules and cell-penetrating peptides led to a readily observable phenotype, indicating significant potential of the developed platform as a robust tool for cell-based drug screening.

High-speed Fourier ptychographic microscopy based on programmable annular illuminations

High-throughput quantitative phase imaging (QPI) is essential to cellular phenotypes characterization as it allows high-content cell analysis and avoids adverse effects of staining reagents on cellular viability and cell signaling. Among different approaches, Fourier ptychographic microscopy (FPM) is probably the most promising technique to realize high-throughput QPI by synthesizing a wide-field, high-resolution complex image from multiple angle-variably illuminated, low-resolution images. However, the large dataset requirement in conventional FPM significantly limits its imaging speed, resulting in low temporal throughput. Moreover, the underlying theoretical mechanism as well as optimum illumination scheme for high-accuracy phase imaging in FPM remains unclear. Herein, we report a high-speed FPM technique based on programmable annular illuminations (AIFPM). The optical-transfer-function (OTF) analysis of FPM reveals that the low-frequency phase information can only be correctly recovered if the LEDs are precisely located at the edge of the objective numerical aperture (NA) in the frequency space. By using only 4 low-resolution images corresponding to 4 tilted illuminations matching a 10×, 0.4 NA objective, we present the high-speed imaging results of in vitro Hela cells mitosis and apoptosis at a frame rate of 25 Hz with a full-pitch resolution of 655 nm at a wavelength of 525 nm (effective NA = 0.8) across a wide field-of-view (FOV) of 1.77 mm², corresponding to a space-bandwidth-time product of 411 megapixels per second. Our work reveals an important capability of FPM towards high-speed high-throughput imaging of in vitro live cells, achieving video-rate QPI performance across a wide range of scales, both spatial and temporal.

Quantitative Algorithm-Based Paired Imaging Measurement for Antibody-Triggered Endocytosis in Cultured Cells

Antibody-triggered endocytosis (ATE) is a biological mechanism on which many therapeutic strategies are grounded, such as delivery of antibody-drug conjugates (ADCs). Current methods monitoring ATE include confocal Z-stack analysis, acid wash, antibody quenching, and pH-sensitive dye labeling. However, those generate less quantifiable results with low throughput. Here we report a new method referred to as "paired imaging measurement" to analyze ATE using a quantitative algorithm in conjunction with high-content imaging. With two sequential measurements of cell surface antibody employing live cell staining and total antibody by immunostaining before and after cell permeabilization, intracellular antibody undergoing endocytosis can be quantified indirectly. Antibodies against CD98 and transferrin receptor were tested on hCMEC/D3 and hiPSC-derived endothelial cells. The maximal response and potency of endocytosed antibodies were generated with good assay robustness (Z' > 0.6) and >5-fold signal/background ratio. Antibody endocytosis response ranking is consistent between batches ( R² > 0.9). The obtained results were confirmed by other traditional methods. In conclusion, we have developed a novel method using a quantitative imaging algorithm in conjunction with live cell staining for high-throughput investigation of ATE.

Algorithmic Mapping and Characterization of the Drug-Induced Phenotypic-Response Space of Parasites Causing Schistosomiasis

Neglected tropical diseases, especially those caused by helminths, constitute some of the most common infections of the world's poorest people. Amongst these, schistosomiasis (bilharzia or 'snail fever'), caused by blood flukes of the genus Schistosoma, ranks second only to malaria in terms of human impact: two hundred million people are infected and close to 800 million are at risk of infection. Drug screening against helminths poses unique challenges: the parasite cannot be cloned and is difficult to target using gene knockouts or RNAi. Consequently, both lead identification and validation involve phenotypic screening, where parasites are exposed to compounds whose effects are determined through the analysis of the ensuing phenotypic responses. The efficacy of leads thus identified derives from one or more or even unknown molecular mechanisms of action. The two most immediate and significant challenges that confront the state-of-the-art in this area are: the development of automated and quantitative phenotypic screening techniques and the mapping and quantitative characterization of the totality of phenotypic responses of the parasite. In this paper, we investigate and propose solutions for the latter problem in terms of the following: (1) mathematical formulation and algorithms that allow rigorous representation of the phenotypic response space of the parasite, (2) application of graph-theoretic and network analysis techniques for quantitative modeling and characterization of the phenotypic space, and (3) application of the aforementioned methodology to analyze the phenotypic space of S. mansoni - one of the etiological agents of schistosomiasis, induced by compounds that target its polo-like kinase 1 (PLK 1) gene - a recently validated drug target. In our approach, first, bio-image analysis algorithms are used to quantify the phenotypic responses of different drugs. Next, these responses are linearly mapped into a low- dimensional space using Principle Component Analysis (PCA). The phenotype space is modeled using neighborhood graphs which are used to represent the similarity amongst the phenotypes. These graphs are characterized and explored using network analysis algorithms. We present a number of results related to both the nature of the phenotypic space of the S. mansoni parasite as well as algorithmic issues encountered in constructing and analyzing the phenotypic-response space. In particular, the phenotype distribution of the parasite was found to have a distinct shape and topology. We have also quantitatively characterized the phenotypic space by varying critical model parameters. Finally, these maps of the phenotype space allows visualization and reasoning about complex relationships between putative drugs and their system-wide effects and can serve as a highly efficient paradigm for assimilating and unifying information from phenotypic screens both during lead identification and lead optimization.

Repurposing High-Throughput Image Assays Enables Biological Activity Prediction for Drug Discovery

In both academia and the pharmaceutical industry, large-scale assays for drug discovery are expensive and often impractical, particularly for the increasingly important physiologically relevant model systems that require primary cells, organoids, whole organisms, or expensive or rare reagents. We hypothesized that data from a single high-throughput imaging assay can be repurposed to predict the biological activity of compounds in other assays, even those targeting alternate pathways or biological processes. Indeed, quantitative information extracted from a three-channel microscopy-based screen for glucocorticoid receptor translocation was able to predict assay-specific biological activity in two ongoing drug discovery projects. In these projects, repurposing increased hit rates by 50- to 250-fold over that of the initial project assays while increasing the chemical structure diversity of the hits. Our results suggest that data from high-content screens are a rich source of information that can be used to predict and replace customized biological assays.

NMR-Fragment Based Virtual Screening: A Brief Overview

Fragment-based drug discovery (FBDD) using NMR has become a central approach over the last twenty years for development of small molecule inhibitors against biological macromolecules, to control a variety of cellular processes. Yet, several considerations should be taken into account for obtaining a therapeutically relevant agent. In this review, we aim to list the considerations that make NMR fragment screening a successful process for yielding potent inhibitors. Factors that may govern the competence of NMR in fragment based drug discovery are discussed, as well as later steps that involve optimization of hits obtained by NMR-FBDD.

New therapeutic approaches for Krabbe disease: The potential of pharmacological chaperones

Missense mutations in the lysosomal hydrolase β‐galactocerebrosidase (GALC) account for at least 40% of known cases of Krabbe disease (KD). Most of these missense mutations are predicted to disrupt the fold of the enzyme, preventing GALC in sufficient amounts from reaching its site of action in the lysosome. The predominant central nervous system (CNS) pathology and the absence of accumulated primary substrate within the lysosome mean that strategies used to treat other lysosomal storage disorders (LSDs) are insufficient in KD, highlighting the still unmet clinical requirement for successful KD therapeutics. Pharmacological chaperone therapy (PCT) is one strategy being explored to overcome defects in GALC caused by missense mutations. In recent studies, several small‐molecule inhibitors have been identified as promising chaperone candidates for GALC. This Review discusses new insights gained from these studies and highlights the importance of characterizing both the chaperone interaction and the underlying mutation to define properly a responsive population and to improve the translation of existing lead molecules into successful KD therapeutics. We also highlight the importance of using multiple complementary methods to monitor PCT effectiveness. Finally, we explore the exciting potential of using combination therapy to ameliorate disease through the use of PCT with existing therapies or with more generalized therapeutics, such as proteasomal inhibition, that have been shown to have synergistic effects in other LSDs. This, alongside advances in CNS delivery of recombinant enzyme and targeted rational drug design, provides a promising outlook for the development of KD therapeutics. © 2016 The Authors. Journal of Neuroscience Research Published by Wiley Periodicals, Inc.

Colony Lysate Arrays for Proteomic Profiling of Drug-Tolerant Persisters of Cancer Cell

Functional heterogeneity of cancer cells is one of the key properties to understanding relapse after drug treatment. Hence, clarification is needed with regard to which types of subgroups of cancer cells dominantly contribute to the initiation of relapse. Recently, we established the colony lysate array (CoLA), which is a method that allows comparison of individual colonies at the protein level to assess the initiation of anticancer drug-tolerant persisters (DTPs) based on the reverse-phase protein array (RPPA) system. DTPs grow in various drug concentrations and types showing 2-dimensional growth (∼1 mm) on a flat surface. The size of DTPs are larger than spheroids (∼0.3 mm) in agarose gel, which makes them easy to handle for a number of assays. DTPs provide functional information during the process of their formation, initiating from the origin of a drug-tolerant single cell. Using >2000 DTPs generated from various drugs and doses profiled on the basis of 44 proteins, we demonstrate that the DTPs are clustered on the basis of their proteomic profiles changing in response to drugs and doses. Of interest, nine transcription factors in the DTPs, such as STAT3 and OCT4A, were identified as having decreased or increased levels of proteins in response to gefitinib. Importantly, these results can be obtained only by individual proteomic colony profiling, which may identify alternative therapeutic targets and biomarkers for DTPs that may harbor critical mechanisms for cancer relapse.

Image-Based Phenotypic Screening with Human Primary T Cells Using One-Dimensional Imaging Cytometry with Self-Tuning Statistical-Gating Algorithms

The parallel microfluidic cytometer (PMC) is an imaging flow cytometer that operates on statistical analysis of low-pixel-count, one-dimensional (1D) line scans. It is highly efficient in data collection and operates on suspension cells. In this article, we present a supervised automated pipeline for the PMC that minimizes operator intervention by incorporating multivariate logistic regression for data scoring. We test the self-tuning statistical algorithms in a human primary T-cell activation assay in flow using nuclear factor of activated T cells (NFAT) translocation as a readout and readily achieve an average Z' of 0.55 and strictly standardized mean difference of 13 with standard phorbol myristate acetate/ionomycin induction. To implement the tests, we routinely load 4 µL samples and can readout 3000 to 9000 independent conditions from 15 mL of primary human blood (buffy coat fraction). We conclude that the new technology will support primary-cell protein-localization assays and "on-the-fly" data scoring at a sample throughput of more than 100,000 wells per day and that it is, in principle, consistent with a primary pharmaceutical screen.

Large population cell characterization using quantitative phase cytometer

A major challenge in cellular analysis is the phenotypic characterization of large cell populations within a short period of time. Among various parameters for cell characterization, the cell dry mass is often used to describe cell size but is difficult to be measured directly with traditional techniques. Here, we propose an interferometric approach based on line-focused beam illumination for high-content precision dry mass measurements of adherent cells in a non-invasive fashion-we call it quantitative phase cytometry (QPC). Besides dry mass, abundant cellular morphological features such as projected area, sphericity, and phase skewness can be readily extracted from the QPC interferometric data. To validate the utility of our technique, we demonstrate characterizing a large population of ∼10⁴ HeLa cells. Our reported QPC system is envisioned as a promising quantitative tool for label-free characterization of a large cell count at single cell resolution. © 2017 International Society for Advancement of Cytometry.

High-content screening identifies inhibitors of the nuclear translocation of ATF6

Activating transcription factor 6 (ATF6) is a transmembrane protein that consists of a cytoplasmic domain and an endoplasmic reticulum (ER) luminal domain. As unfolded protein levels arise in the ER, the ER cytoplasmic domain of ATF6 moves to the nucleus, where it activates the transcription of a range of genes, including those involved in apoptosis. As ATF6 only becomes functional once it has moved to the nucleus, compounds that inhibit its re-localization are of therapeutic interest. The aim of the present study was to rapidly and accurately identify such compounds using a novel image‑based, high‑content screening (HCS) technique. The results from the HCS analysis were then confirmed by luciferase reporter assays, western blot analysis and the measurement of cell viability. We found that HCS identified compounds which inhibited ATF6 nuclear translocation with high specificity, as confirmed by the luciferase reporter assay and western blot analysis. Moreover, we demonstrated that 3 of the 80 identified compounds impaired ATF6-mediated induced cell death. The data from this study support the theory that HCS is a novel, high throughput method which can be used for accurate and rapid compound screening.

Compressive sensing based high-speed time-stretch optical microscopy for two-dimensional image acquisition

In this paper, compressive sensing based high-speed time-stretch optical microscopy for two-dimensional (2D) image acquisition is proposed and experimentally demonstrated for the first time. A section of dispersion compensating fiber (DCF) is used to perform wavelength-to-time conversion and then ultrafast spectral shaping of broadband optical pulses can be achieved via high-speed intensity modulation. A 2D spatial disperser comprising a pair of orthogonally oriented dispersers is employed to produce spatially structured illumination for 2D image acquisition and a section of single mode fiber (SMF) is utilized for pulse compression in the optical domain. In our scheme, a 1.2-GHz photodetector and a 50-MHz analog-to-digital converter (ADC) are used to acquire the energy of the compressed pulses. Image reconstructions are demonstrated at a frame rate of 500 kHz and a sixteen-fold image compression is achieved in our proof-of-concept demonstration.

Development of an image-based screening system for inhibitors of the plastidial MEP pathway and of protein geranylgeranylation

In a preceding study we have recently established an in vivo visualization system for the geranylgeranylation of proteins in a stably transformed tobacco BY-2 cell line, which involves expressing a dexamethasone-inducible GFP fused to the prenylable, carboxy-terminal basic domain of the rice calmodulin CaM61, which naturally bears a CaaL geranylgeranylation motif (GFP-BD-CVIL). By using pathway-specific inhibitors it was there demonstrated that inhibition of the methylerythritol phosphate (MEP) pathway with oxoclomazone and fosmidomycin, as well as inhibition of protein geranylgeranyl transferase type 1 (PGGT-1), shifted the localization of the GFP-BD-CVIL protein from the membrane to the nucleus. In contrast, the inhibition of the mevalonate (MVA) pathway with mevinolin did not affect this localization. Furthermore, in this initial study complementation assays with pathway-specific intermediates confirmed that the precursors for the cytosolic isoprenylation of this fusion protein are predominantly provided by the MEP pathway. In order to optimize this visualization system from a more qualitative assay to a statistically trustable medium or a high-throughput screening system, we established now new conditions that permit culture and analysis in 96-well microtiter plates, followed by fluorescence microscopy. For further refinement, the existing GFP-BD-CVIL cell line was transformed with an estradiol-inducible vector driving the expression of a RFP protein, C-terminally fused to a nuclear localization signal (NLS-RFP). We are thus able to quantify the total number of viable cells versus the number of inhibited cells after various treatments. This approach also includes a semi-automatic counting system, based on the freely available image processing software. As a result, the time of image analysis as well as the risk of user-generated bias is reduced to a minimum. Moreover, there is no cross-induction of gene expression by dexamethasone and estradiol, which is an important prerequisite for this test system.

Total internal reflection fluorescence quantification of receptor pharmacology

Total internal reflection fluorescence (TIRF) microscopy has been widely used as a single molecule imaging technique to study various fundamental aspects of cell biology, owing to its ability to selectively excite a very thin fluorescent volume immediately above the substrate on which the cells are grown. However, TIRF microscopy has found little use in high content screening due to its complexity in instrumental setup and experimental procedures. Inspired by the recent demonstration of label-free evanescent wave biosensors for cell phenotypic profiling and drug screening with high throughput, we had hypothesized and demonstrated that TIRF imaging is also amenable to receptor pharmacology profiling. This paper reviews key considerations and recent applications of TIRF imaging for pharmacology profiling.

Development of an image-based screening system for inhibitors of the plastidial MEP pathway and of protein geranylgeranylation

We have recently established an in vivo visualization system for the geranylgeranylation of proteins in a stably transformed tobacco BY-2 cell line, which involves expressing a dexamethasone-inducible GFP fused to the prenylable, carboxy-terminal basic domain of the rice calmodulin CaM61, which naturally bears a CaaL geranylgeranylation motif (GFP-BD-CVIL). By using pathway-specific inhibitors it was demonstrated that inhibition of the methylerythritol phosphate (MEP) pathway with oxoclomazone and fosmidomycin, as well as inhibition of protein geranylgeranyl transferase type 1 (PGGT-1), shifted the localization of the GFP-BD-CVIL protein from the membrane to the nucleus. In contrast, the inhibition of the mevalonate (MVA) pathway with mevinolin did not affect this localization. Furthermore, complementation assays with pathway-specific intermediates confirmed that the precursors for the cytosolic isoprenylation of this fusion protein are predominantly provided by the MEP pathway. In order to optimize this visualization system from a more qualitative assay to a statistically trustable medium or a high-throughput screening system, we established new conditions that permit culture and analysis in 96-well microtiter plates, followed by fluorescence microscopy. For further refinement, the existing GFP-BD-CVIL cell line was transformed with an estradiol-inducible vector driving the expression of a RFP protein, C-terminally fused to a nuclear localization signal (NLS-RFP). We are thus able to quantify the total number of viable cells versus the number of inhibited cells after various treatments. This approach also includes a semi-automatic counting system, based on the freely available image processing software. As a result, the time of image analysis as well as the risk of user-generated bias is reduced to a minimum. Moreover, there is no cross-induction of gene expression by dexamethasone and estradiol, which is an important prerequisite for this test system.

A multistaged automatic restoration of noisy microscopy cell images

Automated cell segmentation for microscopy cell images has recently become an initial step for further image analysis in cell biology. However, microscopy cell images are easily degraded by noise during the readout procedure via optical-electronic imaging systems. Such noise degradations result in low signal-to-noise ratio (SNR) and poor image quality for cell identification. In order to improve SNR for subsequent segmentation and image-based quantitative analysis, the commonly used state-of-art restoration techniques are applied but few of them are suitable for corrupted microscopy cell images. In this paper, we propose a multistaged method based on a novel integration of trend surface analysis, quantile-quantile plot, bootstrapping, and the Gaussian spatial kernel for the restoration of noisy microscopy cell images. We show this multistaged approach achieves higher performance compared with other state-of-art restoration techniques in terms of peak signal-to-noise ratio and structure similarity in synthetic noise experiments. This paper also reports an experiment on real noisy microscopy data which demonstrated the advantages of the proposed restoration method for improving segmentation performance.

Development and validation of a high-throughput anti-Wolbachia whole-cell screen: a route to macrofilaricidal drugs against onchocerciasis and lymphatic filariasis

There is an urgent need to develop new, safe, and affordable macrofilaricidal drugs for onchocerciasis and lymphatic filariasis treatment and control. The Anti-Wolbachia Consortium (A·WOL) aims to provide a novel treatment with macrofilaricidal activity by targeting the essential bacterial symbiont Wolbachia. The consortium is currently screening a diverse range of compounds to find new chemical space to drive this drug discovery initiative and address this unmet demand. To increase the throughput and capacity of the A·WOL cell-based screen, we have developed a 384-well format assay using a high-content imaging system (Operetta) in conjunction with optimized Wolbachia growth dynamics in the C6/36 Aedes albopictus mosquito cell line. This assay uses texture analysis of cells stained with SYTO 11 as a direct measure of bacterial load. This validated assay has dramatically increased the capacity and throughput of the A·WOL compound library screening program 25-fold, enriching the number of new anti-Wolbachia hits identified for further development as potential macrofilaricides for onchocerciasis and lymphatic filariasis.

Automated image-based assay for evaluation of HIV neutralization and cell-to-cell fusion inhibition

Background

Standardized techniques to detect HIV-neutralizing antibody responses are of great importance in the search for an HIV vaccine.

Methods

Here, we present a high-throughput, high-content automated plaque reduction (APR) assay based on automated microscopy and image analysis that allows evaluation of neutralization and inhibition of cell-cell fusion within the same assay. Neutralization of virus particles is measured as a reduction in the number of fluorescent plaques, and inhibition of cell-cell fusion as a reduction in plaque area.

Results

We found neutralization strength to be a significant factor in the ability of virus to form syncytia. Further, we introduce the inhibitory concentration of plaque area reduction (ICpar) as an additional measure of antiviral activity, i.e. fusion inhibition.

Conclusions

We present an automated image based high-throughput, high-content HIV plaque reduction assay. This allows, for the first time, simultaneous evaluation of neutralization and inhibition of cell-cell fusion within the same assay, by quantifying the reduction in number of plaques and mean plaque area, respectively. Inhibition of cell-to-cell fusion requires higher quantities of inhibitory reagent than inhibition of virus neutralization.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2334-14-472) contains supplementary material, which is available to authorized users.

Automated imaging and other developments in whole-organism anthelmintic screening

Helminth infections still represent a huge public health problem throughout the developing world and in the absence of vaccines control is based on periodic mass drug administration. Poor efficacy of some anthelmintics and concerns about emergence of drug resistance has highlighted the need for new drug discovery. Most current anthelmintics were discovered through in vivo screening of selected compounds in animal models but recent approaches have shifted towards screening for activity against adult or larval stages in vitro. Larvae are normally available in greater numbers than adults, can often be produced in vitro and are small enough for microplate assays. However, the manual visualization of drug effects in vitro is subjective, laborious and slow. This can be overcome by application of automated readouts including high-content imaging. Incorporated into robotically controlled HTS platforms such methods allow the very large compound collections being made available by the pharmaceutical industry or academic organizations to be screened against helminths for the first time, invigorating the drug discovery pipeline. Here, we review the status of whole-organism screens based on in vitro activity against living worms and highlight the recent progress towards automated image-based readouts.

Morphological Effects of Natural Products on Schizosaccharomyces pombe Measured by Imaging Flow Cytometry

ABSTRACT

Gaining a full understanding of the mechanisms of action of natural products as therapeutic agents includes observing the effects of natural products on cellular morphology, because abnormal cellular morphology is an important aspect of cellular transformations that occur as part of disease states. In this study a set of natural products was examined in search of small molecules that influence the cylindrical morphology of fission yeast Schizosaccharomyces pombe. Imaging flow cytometry of large populations of S. pombe exposed to natural products captured cell images and revealed changes in mean length and aspect ratio of cells. Several natural products were found to alter S. pombe's morphology relative to control, in terms of elongating cells, shrinking them, or making them more round. These results may facilitate future investigations into methods by which cells establish and maintain specific shapes.

GRAPHICAL ABSTRACT

Gaining a full understanding of the mechanisms of action of natural products as therapeutic agents includes observing the effects of natural products on cellular morphology, because abnormal cellular morphology is an important aspect of cellular transformations that occur as part of disease states. In this study a set of natural products was examined in search of small molecules that influence the cylindrical morphology of fission yeast Schizosaccharomyces pombe. Imaging flow cytometry of large populations of S. pombe exposed to natural products captured cell images and revealed changes in mean length and aspect ratio of cells. Several natural products were found to alter S. pombe's morphology relative to control, in terms of elongating cells, shrinking them, or making them more round. These results may facilitate future investigations into methods by which cells establish and maintain specific shapes.

Systematic, spatial imaging of large multimolecular assemblies and the emerging principles of supramolecular order in biological systems

Understanding biological systems at the level of their relational (emergent) molecular properties in functional protein networks relies on imaging methods, able to spatially resolve a tissue or a cell as a giant, non-random, topologically defined collection of interacting supermolecules executing myriads of subcellular mechanisms. Here, the development and findings of parameter-unlimited functional super-resolution microscopy are described-a technology based on the fluorescence imaging cycler (IC) principle capable of co-mapping thousands of distinct biomolecular assemblies at high spatial resolution and differentiation (<40 nm distances). It is shown that the subcellular and transcellular features of such supermolecules can be described at the compositional and constitutional levels; that the spatial connection, relational stoichiometry, and topology of supermolecules generate hitherto unrecognized functional self-segmentation of biological tissues; that hierarchical features, common to thousands of simultaneously imaged supermolecules, can be identified; and how the resulting supramolecular order relates to spatial coding of cellular functionalities in biological systems. A large body of observations with IC molecular systems microscopy collected over 20 years have disclosed principles governed by a law of supramolecular segregation of cellular functionalities. This pervades phenomena, such as exceptional orderliness, functional selectivity, combinatorial and spatial periodicity, and hierarchical organization of large molecular systems, across all species investigated so far. This insight is based on the high degree of specificity, selectivity, and sensitivity of molecular recognition processes for fluorescence imaging beyond the spectral resolution limit, using probe libraries controlled by ICs.

Chip-scale fluorescence microscope based on a silo-filter complementary metal-oxide semiconductor image sensor

We demonstrate a silo-filter (SF) complementary metal-oxide semiconductor (CMOS) image sensor for a chip-scale fluorescence microscope. The extruded pixel design with metal walls between neighboring pixels guides fluorescence emission through the thick absorptive filter to the photodiode of a pixel. Our prototype device achieves 13 μm resolution over a wide field of view (4.8 mm × 4.4 mm). We demonstrate bright-field and fluorescence longitudinal imaging of living cells in a compact, low-cost configuration.

Microplate-compatible total internal reflection fluorescence microscopy for receptor pharmacology

We report the use of total internal reflection fluorescence (TIRF) microscopy for analyzing receptor pharmacology and the development of a microplate-compatible TIRF imaging system. Using stably expressed green fluorescence protein tagged β₂-adrenergic receptor as the reporter, we found that the activation of different receptors results in distinct kinetic signatures of the TIRF intensity of cells. These TIRF signatures closely resemble the characteristics of their respective label-free dynamic mass redistribution signals in the same cells. This suggests that TIRF in microplate can be used for profiling and screening drugs.

Optical systems for single cell analyses

BACKGROUND

Data extracted from a population of cells represent the average response from all cells within the population. Even when the cells are genetically identical, cell-to-cell variations and genetic noise can make the cells respond in completely different ways. To understand the mechanisms behind the behaviour of a population, the cells must also be analysed on an individual basis.

OBJECTIVE

This review highlights the use of optical manipulation, microfluidics and advanced fluorescence imaging techniques for the acquisition of single cell data.

CONCLUSION

By implementation of these three techniques, it is possible to achieve a deeper insight into the principles underlying cellular functioning and a more thorough understanding of the phenomena often observed in cell populations, thus facilitating research in drug discovery.

Microfluidic platforms for RNA interference screening of virus-host interactions

RNA interference (RNAi) is a powerful tool for functional genomics with the capacity to comprehensively analyze host-pathogen interactions. High-throughput RNAi screening is used to systematically perturb cellular pathways and discover therapeutic targets, but the method can be tedious and requires extensive capital equipment and expensive reagents. To aid in the development of an inexpensive miniaturized RNAi screening platform, we have developed a two part microfluidic system for patterning and screening gene targets on-chip to examine cellular pathways involved in virus entry and infection. First, a multilayer polydimethylsiloxane (PDMS)-based spotting device was used to array siRNA molecules into 96 microwells targeting markers of endocytosis, along with siRNA controls. By using a PDMS-based spotting device, we remove the need for a microarray printer necessary to perform previously described small scale (e.g. cellular microarrays) and microchip-based RNAi screening, while still minimizing reagent usage tenfold compared to conventional screening. Second, the siRNA spotted array was transferred to a reversibly sealed PDMS-based screening platform containing microchannels designed to enable efficient cell loading and transfection of mammalian cells while preventing cross-contamination between experimental conditions. Validation of the screening platform was examined using Vesicular stomatitis virus and emerging pathogen Rift Valley fever virus, which demonstrated virus entry pathways of clathrin-mediated endocytosis and caveolae-mediated endocytosis, respectively. The techniques here are adaptable to other well-characterized infection pathways with a potential for large scale screening in high containment biosafety laboratories.

Imaging flow cytometry: coping with heterogeneity in biological systems

Imaging flow cytometry (IFC) platforms combine features of flow cytometry and fluorescent microscopy with advances in data-processing algorithms. IFC allows multiparametric fluorescent and morphological analysis of thousands of cellular events and has the unique capability of identifying collected events by their real images. IFC allows the analysis of heterogeneous cell populations, where one of the cellular components has low expression (<0.03%) and can be described by Poisson distribution. With the help of IFC, one can address a critical question of statistical analysis of subcellular distribution of proteins in a cell. Here the authors review advantages of IFC in comparison with more traditional technologies, such as Western blotting and flow cytometry (FC), as well as new high-throughput fluorescent microscopy (HTFM), and discuss further developments of this novel analytical technique.

A multi-functional imaging approach to high-content protein interaction screening

Functional imaging can provide a level of quantification that is not possible in what might be termed traditional high-content screening. This is due to the fact that the current state-of-the-art high-content screening systems take the approach of scaling-up single cell assays, and are therefore based on essentially pictorial measures as assay indicators. Such phenotypic analyses have become extremely sophisticated, advancing screening enormously, but this approach can still be somewhat subjective. We describe the development, and validation, of a prototype high-content screening platform that combines steady-state fluorescence anisotropy imaging with fluorescence lifetime imaging (FLIM). This functional approach allows objective, quantitative screening of small molecule libraries in protein-protein interaction assays. We discuss the development of the instrumentation, the process by which information on fluorescence resonance energy transfer (FRET) can be extracted from wide-field, acceptor fluorescence anisotropy imaging and cross-checking of this modality using lifetime imaging by time-correlated single-photon counting. Imaging of cells expressing protein constructs where eGFP and mRFP1 are linked with amino-acid chains of various lengths (7, 19 and 32 amino acids) shows the two methodologies to be highly correlated. We validate our approach using a small-scale inhibitor screen of a Cdc42 FRET biosensor probe expressed in epidermoid cancer cells (A431) in a 96 microwell-plate format. We also show that acceptor fluorescence anisotropy can be used to measure variations in hetero-FRET in protein-protein interactions. We demonstrate this using a screen of inhibitors of internalization of the transmembrane receptor, CXCR4. These assays enable us to demonstrate all the capabilities of the instrument, image processing and analytical techniques that have been developed. Direct correlation between acceptor anisotropy and donor FLIM is observed for FRET assays, providing an opportunity to rapidly screen proteins, interacting on the nano-meter scale, using wide-field imaging.

Getting the whole picture: combining throughput with content in microscopy

The increasing availability and performance of automated scientific equipment in the past decades have brought about a revolution in the biological sciences. The ease with which data can now be generated has led to a new culture of high-throughput science, in which new types of biological questions can be asked and tackled in a systematic and unbiased manner. High-throughput microscopy, also often referred to as high-content screening (HCS), allows acquisition of systematic data at the single-cell level. Moreover, it allows the visualization of an enormous array of cellular features and provides tools to quantify a large number of parameters for each cell. These features make HCS a powerful method to create data that is rich and biologically meaningful without compromising systematic capabilities. In this Commentary, we will discuss recent work, which has used HCS, to demonstrate the diversity of applications and technological solutions that are evolving in this field. Such advances are placing HCS methodologies at the frontier of high-throughput science and enable scientists to combine throughput with content to address a variety of cell biological questions.

WHIDE--a web tool for visual data mining colocation patterns in multivariate bioimages

Motivation: Bioimaging techniques rapidly develop toward higher resolution and dimension. The increase in dimension is achieved by different techniques such as multitag fluorescence imaging, Matrix Assisted Laser Desorption / Ionization (MALDI) imaging or Raman imaging, which record for each pixel an N-dimensional intensity array, representing local abundances of molecules, residues or interaction patterns. The analysis of such multivariate bioimages (MBIs) calls for new approaches to support users in the analysis of both feature domains: space (i.e. sample morphology) and molecular colocation or interaction. In this article, we present our approach WHIDE (Web-based Hyperbolic Image Data Explorer) that combines principles from computational learning, dimension reduction and visualization in a free web application.

Results: We applied WHIDE to a set of MBI recorded using the multitag fluorescence imaging Toponome Imaging System. The MBI show field of view in tissue sections from a colon cancer study and we compare tissue from normal/healthy colon with tissue classified as tumor. Our results show, that WHIDE efficiently reduces the complexity of the data by mapping each of the pixels to a cluster, referred to as Molecular Co-Expression Phenotypes and provides a structural basis for a sophisticated multimodal visualization, which combines topology preserving pseudocoloring with information visualization. The wide range of WHIDE's applicability is demonstrated with examples from toponome imaging, high content screens and MALDI imaging (shown in the Supplementary Material).

Availability and implementation: The WHIDE tool can be accessed via the BioIMAX website http://ani.cebitec.uni-bielefeld.de/BioIMAX/; Login: whidetestuser; Password: whidetest.

Supplementary information:Supplementary data are available at Bioinformatics online.

Contact:tim.nattkemper@uni-bielefeld.de

RAMTaB: robust alignment of multi-tag bioimages

Background

In recent years, new microscopic imaging techniques have evolved to allow us to visualize several different proteins (or other biomolecules) in a visual field. Analysis of protein co-localization becomes viable because molecules can interact only when they are located close to each other. We present a novel approach to align images in a multi-tag fluorescence image stack. The proposed approach is applicable to multi-tag bioimaging systems which (a) acquire fluorescence images by sequential staining and (b) simultaneously capture a phase contrast image corresponding to each of the fluorescence images. To the best of our knowledge, there is no existing method in the literature, which addresses simultaneous registration of multi-tag bioimages and selection of the reference image in order to maximize the overall overlap between the images.

Methodology/Principal Findings

We employ a block-based method for registration, which yields a confidence measure to indicate the accuracy of our registration results. We derive a shift metric in order to select the Reference Image with Maximal Overlap (RIMO), in turn minimizing the total amount of non-overlapping signal for a given number of tags. Experimental results show that the Robust Alignment of Multi-Tag Bioimages (RAMTaB) framework is robust to variations in contrast and illumination, yields sub-pixel accuracy, and successfully selects the reference image resulting in maximum overlap. The registration results are also shown to significantly improve any follow-up protein co-localization studies.

Conclusions

For the discovery of protein complexes and of functional protein networks within a cell, alignment of the tag images in a multi-tag fluorescence image stack is a key pre-processing step. The proposed framework is shown to produce accurate alignment results on both real and synthetic data. Our future work will use the aligned multi-channel fluorescence image data for normal and diseased tissue specimens to analyze molecular co-expression patterns and functional protein networks.

Next-generation biomarkers based on 100-parameter functional super-resolution microscopy TIS

Functional super-resolution (fSR) microscopy is based on the automated toponome imaging system (TIS). fSR-TIS provides insight into the myriad of different cellular functionalities by direct imaging of large subcellular protein networks in morphologically intact cells and tissues, referred to as the toponome. By cyclical fluorescence imaging of at least 100 molecular cell components, fSR-TIS overcomes the spectral limitations of fluorescence microscopy, which is the essential condition for the detection of protein network structures in situ/in vivo. The resulting data sets precisely discriminate between cell types, subcellular structures, cell states and diseases (fSR). With up to 16 bits per protein, the power of combinatorial molecular discrimination (PCMD) is at least 2(100) per subcellular data point. It provides the dimensionality necessary to uncover thousands of distinct protein clusters including their subcellular hierarchies controlling protein network topology and function in the one cell or tissue section. Here we review the technology and findings showing that functional protein networks of the cell surface in different cancers encompass the same hierarchical and spatial coding principle, but express cancer-specific toponome codes within that scheme (referred to as TIS codes). Findings suggest that TIS codes, extracted from large-scale toponome data, have the potential to be next-generation biomarkers because of their cell type and disease specificity. This is functionally substantiated by the observation that blocking toponome-specific lead proteins results in disassembly of molecular networks and loss of function.

Automated analysis of time-lapse imaging of nuclear translocation by retrospective strategy and its application to STAT1 in HeLa cells

Cell-based image analysis of time-lapse imaging is mainly challenged by faint fluorescence and dim boundaries of cellular structures of interest. To resolve these bottlenecks, a novel method was developed based on “retrospective” analysis for cells undergoing minor morphological changes during time-lapse imaging. We fixed and stained the cells with a nuclear dye at the end of the experiment, and processed the time-lapse images using the binary masks obtained by segmenting the nuclear-stained image. This automated method also identifies cells that move during the time-lapse imaging, which is a factor that could influence the kinetics measured for target proteins that are present mostly in the cytoplasm. We then validated the method by measuring interferon gamma (IFNγ) induced signal transducers and activators of transcription 1 (STAT1) nuclear translocation in living HeLa cells. For the first time, automated large-scale analysis of nuclear translocation in living cells was achieved by our novel method. The responses of the cells to IFNγ exhibited a significant drift across the population, but common features of the responses led us to propose a three-stage model of STAT1 import. The simplicity and automation of this method should enable its application in a broad spectrum of time-lapse studies of nuclear-cytoplasmic translocation.