Optimizing the Cell Painting assay for image-based profiling.

In image-based profiling, software extracts thousands of morphological features of cells from multi-channel fluorescence microscopy images, yielding single-cell profiles that can be used for basic research and drug discovery. Powerful applications have been proven, including clustering chemical and genetic perturbations on the basis of their similar morphological impact, identifying disease phenotypes by observing differences in profiles between healthy and diseased cells and predicting assay outcomes by using machine learning, among many others. Here, we provide an updated protocol for the most popular assay for image-based profiling, Cell Painting. Introduced in 2013, it uses six stains imaged in five channels and labels eight diverse components of the cell: DNA, cytoplasmic RNA, nucleoli, actin, Golgi apparatus, plasma membrane, endoplasmic reticulum and mitochondria. The original protocol was updated in 2016 on the basis of several years' experience running it at two sites, after optimizing it by visual stain quality. Here, we describe the work of the Joint Undertaking for Morphological Profiling Cell Painting Consortium, to improve upon the assay via quantitative optimization by measuring the assay's ability to detect morphological phenotypes and group similar perturbations together. The assay gives very robust outputs despite various changes to the protocol, and two vendors' dyes work equivalently well. We present Cell Painting version 3, in which some steps are simplified and several stain concentrations can be reduced, saving costs. Cell culture and image acquisition take 1-2 weeks for typically sized batches of ≤20 plates; feature extraction and data analysis take an additional 1-2 weeks.This protocol is an update to Nat. Protoc. 11, 1757-1774 (2016): https://doi.org/10.1038/nprot.2016.105.

Rapid 3D phenotypic analysis of neurons and organoids using data-driven cell segmentation-free machine learning.

Phenotypic profiling of large three-dimensional microscopy data sets has not been widely adopted due to the challenges posed by cell segmentation and feature selection. The computational demands of automated processing further limit analysis of hard-to-segment images such as of neurons and organoids. Here we describe a comprehensive shallow-learning framework for automated quantitative phenotyping of three-dimensional (3D) image data using unsupervised data-driven voxel-based feature learning, which enables computationally facile classification, clustering and advanced data visualization. We demonstrate the analysis potential on complex 3D images by investigating the phenotypic alterations of: neurons in response to apoptosis-inducing treatments and morphogenesis for oncogene-expressing human mammary gland acinar organoids. Our novel implementation of image analysis algorithms called Phindr3D allowed rapid implementation of data-driven voxel-based feature learning into 3D high content analysis (HCA) operations and constitutes a major practical advance as the computed assignments represent the biology while preserving the heterogeneity of the underlying data. Phindr3D is provided as Matlab code and as a stand-alone program (https://github.com/DWALab/Phindr3D).

A reference library for assigning protein subcellular localizations by image-based machine learning.

Confocal micrographs of EGFP fusion proteins localized at key cell organelles in murine and human cells were acquired for use as subcellular localization landmarks. For each of the respective 789,011 and 523,319 optically validated cell images, morphology and statistical features were measured. Machine learning algorithms using these features permit automated assignment of the localization of other proteins and dyes in both cell types with very high accuracy. Automated assignment of subcellular localizations for model tail-anchored proteins with randomly mutated C-terminal targeting sequences allowed the discovery of motifs responsible for targeting to mitochondria, endoplasmic reticulum, and the late secretory pathway. Analysis of directed mutants enabled refinement of these motifs and characterization of protein distributions in within cellular subcompartments.

Image-Based Analysis of Protein Stability.

Short half-life proteins regulate many essential processes, including cell cycle, transcription, and apoptosis. However, few well-characterized protein-turnover pathways have been identified because traditional methods to measure protein half-life are time and labor intensive. To overcome this barrier, we developed a protein stability probe and high-content screening pipeline for novel regulators of short half-life proteins using automated image analysis. Our pilot probe consists of the short half-life protein c-MYC (MYC) fused to Venus fluorescent protein (MYC-Venus). This probe enables protein half-life to be scored as a function of fluorescence intensity and distribution. Rapid turnover prevents maximal fluorescence of the probe due to the relatively longer maturation time of the fluorescent protein. Cells expressing the MYC-Venus probe were analyzed using a pipeline in which automated confocal microscopy and image analyses were used to score MYC-Venus stability by two strategies: assaying the percentage of cells with Venus fluorescence above background, and phenotypic comparative analysis. To evaluate this high-content screening pipeline and our probe, a kinase inhibitor library was screened by confocal microscopy to identify known and novel kinases that regulate MYC stability. Compounds identified were shown to increase the half-life of both MYC-Venus and endogenous MYC, validating the probe and pipeline. Fusion of another short half-life protein, myeloid cell leukemia 1 (MCL1), with Venus also demonstrated an increase in percent Venus-positive cells after treatment with inhibitors known to stabilize MCL1. Together, the results validate the use of our automated microscopy and image analysis pipeline of stability probe-expressing cells to rapidly and quantitatively identify regulators of short half-life proteins. © 2019 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.

Improving drug discovery using image-based multiparametric analysis of the epigenetic landscape.

High-content phenotypic screening has become the approach of choice for drug discovery due to its ability to extract drug-specific multi-layered data. In the field of epigenetics, such screening methods have suffered from a lack of tools sensitive to selective epigenetic perturbations. Here we describe a novel approach, Microscopic Imaging of Epigenetic Landscapes (MIEL), which captures the nuclear staining patterns of epigenetic marks and employs machine learning to accurately distinguish between such patterns. We validated the MIEL platform across multiple cells lines and using dose-response curves, to insure the fidelity and robustness of this approach for high content high throughput drug discovery. Focusing on noncytotoxic glioblastoma treatments, we demonstrated that MIEL can identify and classify epigenetically active drugs. Furthermore, we show MIEL was able to accurately rank candidate drugs by their ability to produce desired epigenetic alterations consistent with increased sensitivity to chemotherapeutic agents or with induction of glioblastoma differentiation.

Peak emission wavelength and fluorescence lifetime are coupled in far-red, GFP-like fluorescent proteins.

The discovery and use of fluorescent proteins revolutionized cell biology by allowing the visualization of proteins in living cells. Advances in fluorescent proteins, primarily through genetic engineering, have enabled more advanced analyses, including Förster resonance energy transfer (FRET) and fluorescence lifetime imaging microscopy (FLIM) and the development of genetically encoded fluorescent biosensors. These fluorescence protein-based sensors are highly effective in cells grown in monolayer cultures. However, it is often desirable to use more complex models including tissue explants, organoids, xenografts, and whole animals. These types of samples have poor light penetration owing to high scattering and absorption of light by tissue. Far-red light with a wavelength between 650-900nm is less prone to scatter, and absorption by tissues and can thus penetrate more deeply. Unfortunately, there are few fluorescent proteins in this region of the spectrum, and they have sub-optimal fluorescent properties including low brightness and short fluorescence lifetimes. Understanding the relationships between the amino-acid sequences of far-red fluorescence proteins and their photophysical properties including peak emission wavelengths and fluorescence lifetimes would be useful in the design of new fluorescence proteins for this region of the spectrum. We used both site-directed mutagenesis and gene-shuffling between mScarlet and mCardinal fluorescence proteins to create new variants and assess their properties systematically. We discovered that for far-red, GFP-like proteins the emission maxima and fluorescence lifetime have a strong inverse correlation.

Evidence Implicating Immunological Host Effects in the Efficacy of Metronomic Low-Dose Chemotherapy.

Conventional chemotherapy drugs administered at a maximum tolerated dose (MTD) remains the backbone for treating most cancers. Low-dose metronomic (LDM) chemotherapy, which utilizes lower, less toxic, doses given on a close regular basis over prolonged periods, is an alternative and better tolerated potential strategy to improve chemotherapy. LDM chemotherapy has been evaluated preclinically and clinically and has shown therapeutic benefit, in both early and advanced stage metastatic disease, especially when used as a maintenance therapy. However, knowledge about the antitumor mechanisms by which LDM chemotherapy acts remain limited. Here we characterized the effects of LDM and MTD capecitabine therapy on tumor and host cells using high-throughput systems approaches involving mass spectrometry flow cytometry and automated cell imaging followed by in vivo analyses of such therapies. An increase in myeloid and T regulatory cells and a decrease in NK and T cytotoxic cells were found in MTD-capecitabine-treated tumors compared with LDM-capecitbine-treated tumors. Plasma from MTD capecitabine-treated mice induced a more tumorigenic and metastatic profile in both breast and colon carcinoma cells than plasma from mice treated with LDM capecitabine. These results correlated, in part, with in vivo studies using models of human or mouse advanced metastatic disease, where the therapeutic advantage of MTD capecitabine was limited despite a substantial initial antitumor activity found in the primary tumor setting. Overall these results implicate a possible contribution of immunologic host effects in accounting for the therapeutic limitations of MTD compared with LDM capecitabine. Cancer Res; 76(20); 5983-93. ©2016 AACR.

High-content screening identifies kinase inhibitors that overcome venetoclax resistance in activated CLL cells.

Novel agents such as the Bcl-2 inhibitor venetoclax (ABT-199) are changing treatment paradigms for chronic lymphocytic leukemia (CLL) but important problems remain. Although some patients exhibit deep and durable responses to venetoclax as a single agent, other patients harbor subpopulations of resistant leukemia cells that mediate disease recurrence. One hypothesis for the origin of resistance to venetoclax is by kinase-mediated survival signals encountered in proliferation centers that may be unique for individual patients. An in vitro microenvironment model was developed with primary CLL cells that could be incorporated into an automated high-content microscopy-based screen of kinase inhibitors (KIs) to identify agents that may improve venetoclax therapy in a personalized manner. Marked interpatient variability was noted for which KIs were effective; nevertheless, sunitinib was identified as the most common clinically available KI effective in overcoming venetoclax resistance. Examination of the underlying mechanisms indicated that venetoclax resistance may be induced by microenvironmental signals that upregulate antiapoptotic Bcl-xl, Mcl-1, and A1, which can be counteracted more efficiently by sunitinib than by ibrutinib or idelalisib. Although patient-specific drug responses are common, for many patients, combination therapy with sunitinib may significantly improve the therapeutic efficacy of venetoclax.

Tunable hydrogel thin films from reactive synthetic polymers as potential two-dimensional cell scaffolds.

This article describes the formation of cross-linked 10-200-nm-thick polymer hydrogel films by alternating the spin-coating of two mutually reactive polymers from organic solutions, followed by hydrolysis of the resulting multilayer film in aqueous buffer. Poly(methyl vinyl ether-alt-maleic anhydride) (PMM) was deposited from acetonitrile solution, and poly(N-3-aminopropylmethacrylamide-co-N-2-hydroxypropylmethacrylamide) (PAPMx, where x corresponds to the 3-aminopropylmethacrylamide content ranging from 10 to 100%) was deposited from methanol. Multilayer films were formed in up to 20 deposition cycles. The films cross-linked during formation by reaction between the amine groups of PAPMx and the anhydride groups of PMM. The resulting multilayer films were covalently postfunctionalized by exposure to fluoresceinamine, decylamine, d-glucamine, or fluorescently labeled PAPMx solutions prior to the hydrolysis of residual anhydride in aqueous PBS buffer. This allowed tuning the hydrophobicity of the film to give static water contact angles ranging from about 5 to 90°. Increasing the APM content in PAPMx from 10 to 100% led to apparent Young's moduli from 300 to 700 kPa while retaining sufficient anhydride groups to allow postfunctionalization of the films. This allowed the resulting (PMM/PAPMx) multilayer films to be turned into adhesion-promoting or antifouling surfaces for C2C12 mouse myoblasts and MCF 10A premalignant human mammary epithelial cells.

Discovery of Small Molecule Kappa Opioid Receptor Agonist and Antagonist Chemotypes through a HTS and Hit Refinement Strategy.

Herein we present the outcome of a high throughput screening (HTS) campaign-based strategy for the rapid identification and optimization of selective and general chemotypes for both kappa (κ) opioid receptor (KOR) activation and inhibition. In this program, we have developed potent antagonists (IC(50) < 120 nM) or agonists of high binding affinity (K(i) < 3 nM). In contrast to many important KOR ligands, the compounds presented here are highly modular, readily synthesized and, in most cases, achiral. The four new chemotypes hold promise for further development into chemical tools for studying the KOR or as potential therapeutic lead candidates.