An image analysis toolbox for high-throughput C. elegans assays

We present a toolbox for high-throughput screening of image-based Caenorhabditis elegans phenotypes. The image analysis algorithms measure morphological phenotypes in individual worms and are effective for a variety of assays and imaging systems. This WormToolbox is available through the open-source CellProfiler project and enables objective scoring of whole-worm high-throughput image-based assays of C. elegans for the study of diverse biological pathways that are relevant to human disease.National Institutes of Health (U.S.) (U54 EB005149

Straightening Caenorhabditis elegans images

Motivation: Caenorhabditis elegans, a roundworm found in soil, is a widely studied model organism with about 1000 cells in the adult. Producing high-resolution fluorescence images of C.elegans to reveal biological insights is becoming routine, motivating the development of advanced computational tools for analyzing the resulting image stacks. For example, worm bodies usually curve significantly in images. Thus one must ‘straighten’ the worms if they are to be compared under a canonical coordinate system

Celeganser: Automated Analysis of Nematode Morphology and Age

The nematode Caenorhabditis elegans (C. elegans) serves as an important model organism in a wide variety of biological studies. In this paper we introduce a pipeline for automated analysis of C. elegans imagery for the purpose of studying life-span, health-span and the underlying genetic determinants of aging. Our system detects and segments the worm, and predicts body coordinates at each pixel location inside the worm. These coordinates provide dense correspondence across individual animals to allow for meaningful comparative analysis. We show that a model pre-trained to perform body-coordinate regression extracts rich features that can be used to predict the age of individual worms with high accuracy. This lays the ground for future research in quantifying the relation between organs' physiologic and biochemical state, and individual life/health-span.Comment: Computer Vision for Microscopy Image Analysis (CVMI) 202

Quantifying Phenotypic Variation in Isogenic Caenorhabditis elegans Expressing Phsp-16.2::gfp by Clustering 2D Expression Patterns

Isogenic populations of animals still show a surprisingly large amount of phenotypic variation between individuals. Using a GFP reporter that has been shown to predict longevity and resistance to stress in isogenic populations of the nematode Caenorhabditis elegans, we examined residual variation in expression of this GFP reporter. We found that when we separated the populations into brightest 3% and dimmest 3% we also saw variation in relative expression patterns that distinguished the bright and dim worms. Using a novel image processing method which is capable of directly analyzing worm images, we found that bright worms (after normalization to remove variation between bright and dim worms) had expression patterns that correlated with other bright worms but that dim worms fell into two distinct expression patterns. We have analysed a small set of worms with confocal microscopy to validate these findings, and found that the activity loci in these clusters are caused by extremely bright intestine cells. We also found that the vast majority of the fluorescent signal for all worms came from intestinal cells as well, which may indicate that the activity of intestinal cells is responsible for the observed patterns. Phenotypic variation in C. elegans is still not well understood but our proposed novel method to analyze complex expression patterns offers a way to enable a better understanding

Elasticity of semiflexible polymers in two dimensions

We study theoretically the entropic elasticity of a semi-flexible polymer, such as DNA, confined to two dimensions. Using the worm-like-chain model we obtain an exact analytical expression for the partition function of the polymer pulled at one end with a constant force. The force-extension relation for the polymer is computed in the long chain limit in terms of Mathieu characteristic functions. We also present applications to the interaction between a semi-flexible polymer and a nematic field, and derive the nematic order parameter and average extension of the polymer in a strong field.Comment: 16 pages, 3 figure

Automatically tracking feeding behavior in populations of foraging C. elegans

Caenorhabditis elegans feeds on bacteria and other small microorganisms which it ingests using its pharynx, a neuromuscular pump. Currently, measuring feeding behavior requires tracking a single animal, indirectly estimating food intake from population-level metrics, or using restrained animals. To enable large throughput feeding measurements of unrestrained, crawling worms on agarose plates at a single worm resolution, we developed an imaging protocol and a complementary image analysis tool called PharaGlow. We image up to 50 unrestrained crawling worms simultaneously and extract locomotion and feeding behaviors. We demonstrate the tool’s robustness and high-throughput capabilities by measuring feeding in different use-case scenarios, such as through development, with genetic and chemical perturbations that result in faster and slower pumping, and in the presence or absence of food. Finally, we demonstrate that our tool is capable of long-term imaging by showing behavioral dynamics of mating animals and worms with different genetic backgrounds. The low-resolution fluorescence microscopes required are readily available in C. elegans laboratories, and in combination with our python-based analysis workflow makes this methodology easily accessible. PharaGlow therefore enables the observation and analysis of the temporal dynamics of feeding and locomotory behaviors with high-throughput and precision in a user-friendly system.eLife digest: A small worm called C. elegans is constantly hungry. It spends all its time looking for food or eating. Hunger and environmental factors, like light, influence its feeding behavior. Studying these worms has helped scientists learn how feeding affects health, longevity, and aging. Feeding studies might also help scientists learn how the nervous system works and how it controls feeding. Most studies have used one of two approaches. Scientists may measure how much food a group of C. elegans eat by measuring food before and after it is offered to the worms. Or they restrain individual worms and measure the movement of a tube-like muscle, called the pharynx, which the animals use to vacuum up food. Restraining the worms can alter their behavior or brain activity, and studying group feeding habits may miss individual differences, so neither is optimal. Ideally, scientists could measure the feeding activity of many free-ranging worms, but because the movements of the pharynx are small, that too can be a challenge. Bonnard, Liu et al. developed a software tool that automatically detects and measures feeding behavior in a group of about 30 free-ranging C. elegans simultaneously. In the experiments, Bonnard, Liu et al. genetically engineered worms expressing a fluorescent protein in their pharynx, making it possible to measure its movements with a microscope. They used the microscope to capture images of 30-50 animals at a time as they foraged for food in a dish. Then, they used the software to analyze the data they collected. Over three days and five imaging sessions, Bonnard and Liu et al. tracked the feeding behavior of about 1,000 animals under different conditions. The experiments show that the pharynx grows rapidly during early worm development when the worms quadruple their length, but the rate of pharynx muscle contractions stays the same. They also showed the technique could measure feeding behaviors in animals with different genetic backgrounds, ages, or those engaged in behaviors like mating. The tool allows for larger and longer-term studies of worm feeding behaviors than previous approaches. Bonnard, Liu et al. made their software, called PharaGlow, available for use by other researchers. The tool may make feeding measurements a routine part of C. elegans studies. It will allow scientists to gain new insights into the role of feeding in a range of processes, including aging, fitness, mating, and overall health. Follow-up studies could determine if these findings are general strategies that also apply to other animals

A 3D digital atlas of C. elegans and its application to single-cell analyses,”

We built a digital nuclear atlas of the newly hatched, first larval stage (l1) of the wild-type hermaphrodite of Caenorhabditis elegans at single-cell resolution from confocal image stacks of 15 individual worms. the atlas quantifies the stereotypy of nuclear locations and provides other statistics on the spatial patterns of the 357 nuclei that could be faithfully segmented and annotated out of the 558 present at this developmental stage. We then developed an automated approach to assign cell names to each nucleus in a threedimensional image of an l1 worm. We achieved 86% accuracy in identifying the 357 nuclei automatically. this computational method will allow high-throughput single-cell analyses of the post-embryonic worm, such as gene expression analysis, or ablation or stimulation of cells under computer control in a high-throughput functional screen. Despite the detailed knowledge of the anatomy of the nematode C. elegans 1 as well as its determined cell lineage 2,3 , the mapped connectivity of its nervous system 4,5 and its sequenced genome 6,7 , we still lack a three-dimensional (3D) digital atlas of positions of nuclei in any postembryonic stage. Such an atlas has several potential applications. First, it provides us with previously unavailable quantitative knowledge about the degree of stereotypy of the positions of nuclei and the specific spatial relationships between different cells. Second, the atlas can serve as a standard template; we can compare any 3D image of a wild-type C. elegans to the atlas and extract the identities of individual nuclei using an automated approach. This is essential for high-throughput analysis of cellular information such as gene expression at single-cell resolution. Such an analysis provides much richer information than does analysis of expression data from a DNA microarray experiment 8,9 as DNA microarrays reveal average expression from tissue or from the entire individual but not the expression in an individual cell. Prior to this study, the anatomy of C. elegans has been described qualitatively by images with a text description or two-dimensional sketches 10 . Early efforts using electron microscopy analyses have resulted in detailed views of the anatomy 10 and even a connectivity graph of the nervous system 4,5 , but to date, manual or automated segmentation of the fine structure of such an ultrahigh-resolution image stack has not been demonstrated. Whereas one might contemplate carrying out such a manual segmentation for a single worm, doing so for enough worms to deliver statistical information on the location of nuclei is effectively impractical. Our method for automatically analyzing individual cells in postembryonic worms complements the similar capability developed previously for the embryo results Building a 3d digital atlas We used DAPI (4,6-diamidino-2-phenylindole) to stain the nuclei of all 558 cells. We used a myo-3:GFP transgene to label the nuclei of the 81 body wall muscle cells and 1 depressor muscle cell. These nuclei were fiducial markers, used by our manual and automated approach to annotate cells. We used a gene encoding monomeric Cherry protein (mCherry) driven by a promoter from a gene of interest to reveal expression in a set of target cells. We collected 3D images of C. elegans at the L1 stage using a Leica confocal microscope To build a standard digital atlas, we first computationally straightened the curved worm body in the 3D image into a rod shape 1

A Low Percent Ethanol Method for Immobilizing Planarians

Planarians have recently become a popular model system for the study of adult stem cells, regeneration and polarity. The system is attractive for both undergraduate and graduate research labs, since planarian colonies are low cost and easy to maintain. Also in situ hybridization, immunofluorescence and RNA-interference (RNAi) gene knockdown techniques have been developed for planarian studies. However, imaging of live worms (particularly at high magnifications) is difficult because animals are strongly photophobic; they quickly move away from light sources and out of frame. The current methods available to inhibit movement in planarians include RNAi injection and exposure to cold temperatures. The former is labor and time intensive, while the latter precludes the use of many fluorescent reporter dyes. Here, we report a simple, inexpensive and reversible method to immobilize planarians for live imaging. Our data show that a short 1 hour treatment with 3% ethanol (EtOH) is sufficient to inhibit both the fine and gross movements of Schmidtea mediterranea planarians, of the typical size used (4–6 mm), with full recovery of movement within 3–4 hours. Importantly, EtOH treatment did not interfere with regeneration, even after repeated exposure, nor lyse epithelial cells (as assayed by H&E staining). We demonstrate that a short exposure to a low concentration of EtOH is a quick and effective method of immobilizing planarians, one that is easily adaptable to planarians of all sizes and will increase the accessibility of live imaging assays to planarian researchers