Computational methods for image-based profiling are under active development, but their success hinges on assays that can capture a wide range of phenotypes. We have developed a multiplex cytological profiling assay that “paints the cell” with as many fluorescent markers as possible without compromising our ability to extract rich, quantitative profiles in high throughput. The assay detects seven major cellular components. In a pilot screen of bioactive compounds, the assay detected a range of cellular phenotypes and it clustered compounds with similar  annotated protein targets or chemical structure based on cytological profiles. The results demonstrate that the assay captures subtle patterns in the combination of morphological labels, thereby detecting the effects of chemical compounds even though their targets are not stained directly. This image-based assay provides an unbiased approach to characterize compound- and disease-associated cell states to support future probe discovery.

The Bacillus thuringiensis δ-endotoxins (Bt toxins) are widely used insecticidal proteins in engineered crops that provide agricultural, economic, and environmental benefits. The development of insect resistance to Bt toxins endangers their long-term effectiveness. We developed a phage-assisted continuous evolution (PACE) selection that rapidly evolves high-affinity protein-protein interactions, and applied this system to evolve variants of the Bt toxin Cry1Ac that bind a cadherin-like receptor from the insect pest Trichoplusia ni (TnCAD) that is not natively targeted by wild-type Cry1Ac. The resulting evolved Cry1Ac variants bind TnCAD with high affinity (Kd = 11–41 nM), kill TnCAD-expressing insect cells that are not susceptible to wild-type Cry1Ac, and kill Cry1Ac-resistant T. ni insects up to 335-fold more potently than wild-type Cry1Ac. Our findings establish that the evolution of Bt toxins with novel insect cell receptor affinity can overcome Bt toxin resistance in insects and confer lethality approaching that of the wild-type Bt toxin against non-resistant insects.

BackgroundLarge-scale image sets acquired by automated microscopy of perturbed samples enable a detailed comparison of cell states induced by each perturbation, such as a small molecule from a diverse library. Highly multiplexed measurements of cellular morphology can be extracted from each image and subsequently mined for a number of applications.FindingsThis microscopy dataset includes 919 265 five-channel fields of view, representing 30 616 tested compounds, available at “The Cell Image Library” (CIL) repository. It also includes data files containing morphological features derived from each cell in each image, both at the single-cell level and population-averaged (i.e., per-well) level; the image analysis workflows that generated the morphological features are also provided. Quality-control metrics are provided as metadata, indicating fields of view that are out-of-focus or containing highly fluorescent material or debris. Lastly, chemical annotations are supplied for the compound treatments applied.ConclusionsBecause computational algorithms and methods for handling single-cell morphological measurements are not yet routine, the dataset serves as a useful resource for the wider scientific community applying morphological (image-based) profiling. The dataset can be mined for many purposes, including small-molecule library enrichment and chemical mechanism-of-action studies, such as target identification. Integration with genetically perturbed datasets could enable identification of small-molecule mimetics of particular disease- or gene-related phenotypes that could be useful as probes or potential starting points for development of future therapeutics.

High-throughput screening has become a mainstay of small-molecule probe and early drug discovery. The question of how to build and evolve efficient screening collections systematically for cellbased and biochemical screening is still unresolved. It is often assumed that chemical structure diversity leads to diverse biological performance of a library. Here, we confirm earlier results showing that this inference is not always valid and suggest instead using biological measurement diversity derived from multiplexed profiling in the construction of libraries with diverse assay performance patterns for cell-based screens. Rather than using results from tens or hundreds of completed assays, which is resource intensive and not easily extensible, we use high-dimensional image-based cell morphology and gene expression profiles. We piloted this approach using over 30,000 compounds. We show that small-molecule profiling can be used to select compound sets with high rates of activity and diverse biological performance.chemical diversity | biological performance diversity | biological activity | chemical similarity P rofiling small molecules based on multiple biological activity measurements can illuminate mechanisms of action by comparing profiles with compounds whose mechanisms of action are known (1-5). Here, we describe a previously unidentified use of small-molecule profiling-enabling the creation of activityenriched and performance-diverse compound libraries for smallmolecule probe and drug discovery.Biochemical and cell-based high-throughput screening (HTS) is routinely used to discover novel bioactive molecules through unbiased testing of up to several million compounds per screen (6). However, despite ongoing advances in throughput, compound libraries will always represent only a small fraction of all relevant compounds theoretically accessible through chemical synthesis (a concept often referred to as "chemical space") (7). Library composition therefore presents a strong source of bias and potential limitation for any screening endeavor.There is little dissent about the notion that a good screening collection should yield many high-quality hits for a wide range of biological targets or phenotypes. In other words, it should be enriched for bioactive compounds and have high biological performance diversity. A high percentage of compounds lacking any activity will contribute to high cost and low performance of a high-throughput screen. A practical example is a compound collection containing a high percentage of compounds that fail to penetrate cell membranes-such a library will be unlikely to perform effectively in a cell-based HTS exploring an intracellular process. Similarly, a screening collection of compounds with highly redundant biological activities will be less efficient than an equally sized library with diverse performance (Fig. 1). A systematic path to reach these goals, however, remains elusive. One common practice is analyzing structural features of compounds to maximize chemical structural diversity. Ho...

Metal nanoparticles have been studied for their anticoagulant and anti-inflammatory efficacy in various models. Specifically, gold and silver nanoparticles exhibit properties that make these ideal candidates for biological applications. The typical synthesis of gold and silver nanoparticles incorporates contaminants that could pose further problems. Here we demonstrate a clean method of synthesizing gold and silver nanoparticles that exhibit biological functions. These nanoparticles were prepared by reducing AuCl4 and AgNO3 using heparin and hyaluronan, as both reducing and stabilizing agents. The particles show stability under physiological conditions, and narrow size distributions for heparin particles and wider distribution for hyaluronan particles. Studies show that the heparin nanoparticles exhibit anticoagulant properties. Additionally, either gold- or silver- heparin nanoparticles exhibit local anti-inflammatory properties without any significant effect on systemic hemostasis upon administration in carrageenan-induced paw edema models. In conclusion, gold and silver nanoparticles complexed with heparin demonstrated effective anticoagulant and anti-inflammatory efficacy, having potential in various local applications.