Prakash, Deep et al. (2021) International Worm Meeting "Pseudomonas aeruginosa Associated Volatiles Drive Chemotactic Behaviour and Immune Response In C. elegans"

Prakash, Deep, Danggen, Kaling, Singh, Varsha

[International Worm Meeting, 2021]

Olfaction plays an important role in threat perception in higher organisms. To understand the role of olfaction in host survival, we studied interaction of C. elegans with Pseudomonas aeruginosa, a bacterium commonly found in the same ecological niche as this nematode. P. aeruginosa acts as a pathogen against C. elegans, colonizing its gut and reducing its survival. It is known that C. elegans actively detects and avoids P. aeruginosa (Zhang et al. Nature 2005). We have identified two volatiles produced by P. aeruginosa that elicit a behavioural response in C. elegans. One of the chemicals is an attractant and the other is a repellent for C. elegans. The amphid neurons AWA, AWB and AWC are mainly responsible for detecting volatile odorants. While AWA and AWC detect attractants, AWB is responsible for detecting repellents. By studying calcium dynamics in olfactory neurons, we have identified specific neurons which detect volatiles from P. aeruginosa. Through qPCR analysis, we have observed induction of P. aeruginosa specific immune response genes upon exposure to the volatile repellent. The induction of immune response genes is dependent on functional olfactory neurons. Further, pre-exposure of worms to the identified repellent also increases their survival on Pseudomonas aeruginosa lawn. Keywords: Host-microbe interactions, Olfaction, Chemotaxis, Immune response, Pseudomonas aeruginosa, Volatiles

Sapir, Amir et al. (2013) International Worm Meeting "On methane seeps, worms, and parasitic fungi: microsporidia-infected nematodes reveal another secret of the deep sea."

Sapir, Amir, Mundo-Ocampo, Manuel, Dillman, Adler, W. Sternberg, Paul, Orphan, Victoria, Ingels, Jeroen, Baldwin, James, Connon, Stephanie, Levin, Lisa, DeModena, John, Grupe, Benjamin

[International Worm Meeting, 2013]

The deep sea is earth's largest habitat, yet the nature and level of parasitism in this environment are mostly unknown. Here we report the discovery of a fungus-related parasitic microsporidium, Nematocenator marisprofundi that infects nematodes in methane seeps on the Pacific Ocean floor. This infection is species-specific and has been temporally and spatially stable over two years of sampling, indicating an ecologically relevant host-parasite interaction. N. marisprofundi targets the host's body wall muscles causing cell lysis, and in severe infection cases even muscle filament degradation. Phylogenetic analyses place N. marisprofundi as a separate branch among basal microsporidia lineages, suggesting that microsporidia-nematode parasitism occurred in the deep sea early in microsporidia evolution and that N. marisprofundi belongs to a novel and basal deep-sea microsporidian clade. Our findings present a new perspective on the abundance, nature, and ecological significance of deep-sea parasitism by placing nematodes, one of the most abundant animal phyla in many deep-sea settings, as a host for microsporidia parasites. This demonstrates the complexity of methane seep ecosystems being a hub for inter-kingdom interactions between bacteria, nematodes, and parasitic fungi. Our study adds microsporidia parasitism as a previously unknown characteristic of chemoautotrophic methane seep ecosystems and suggests a role for fungal-mediated pathologies in the deep sea.

Fischer, Christian et al. (2021) International Worm Meeting "MitoSegNet: Easy-to-use Deep Learning Segmentation for Analysing Mitochondrial Morphology"

Fischer, Christian, Haeussler, Simon, Marr, Carsten, Duchen, Michael, Conradt, Barbara, Rolland, Stephane, Singh, Kritarth, Besora-Casals, Laura

[International Worm Meeting, 2021]

While the analysis of mitochondrial morphology has emerged as an important tool in the study of mitochondrial function, efficient quantification of mitochondrial microscopy images presents a difficult task and bottleneck for statistically robust conclusions. Here, we present the Mitochondrial Segmentation Network (MitoSegNet), a pretrained deep learning segmentation model that enables researchers to easily exploit the power of deep learning for the quantification of mitochondrial morphology (Fischer, Besora-Casals et al. 2020). The MitoSegNet was generated by training a modified fully convolutional neural network with fluorescent microscopy, maximum-intensity projection images, depicting mitochondria in body wall muscle cells of adult C. elegans worms. We tested the performance of MitoSegNet against three feature-based segmentation algorithms and the machine-learning segmentation tool Ilastik. MitoSegNet outperformed all other methods in both pixelwise and morphological segmentation accuracy. We successfully applied MitoSegNet to unseen fluorescence microscopy images of mitoGFP expressing mitochondria in wild-type and catp-6ATP13A2 mutant C. elegans adults. Additionally, MitoSegNet was capable of accurately segmenting mitochondria in HeLa cells treated with fragmentation inducing reagents. We provide MitoSegNet for all operating systems as an easy-to-use graphical user interface tool that combines segmentation with morphological analysis. Reference Fischer, C. A., L. Besora-Casals, S. G. Rolland, S. Haeussler, K. Singh, M. Duchen, B. Conradt and C. Marr (2020). "MitoSegNet: Easy-to-use Deep Learning Segmentation for Analyzing Mitochondrial Morphology." iScience 23(10).

Chaudhary, Shivesh et al. (2021) International Worm Meeting "Deep learning tools for C. elegans whole-brain imaging"

Moon, Sihoon, Chaudhary, Shivesh, Lu, Hang, Han, Haejun

[International Worm Meeting, 2021]

Advances in deep learning and computer vision have revolutionized analysis of neuron activity and behavioral data. Here we present a deep learning (DL) toolbox - a collection of three deep learning methods to solve challenging problems in C. elegans whole-brain imaging. First, accurate segmentation of densely packed nuclei in fluorescence channels is critical for downstream tasks such as cell tracking, signal extraction and identity annotation. While many deep learning methods are available for 2D images, 3D segmentation methods for highly anisotropic images are not available. We combined a well-known DL framework for instance segmentation in 2D images with optimal transport based clustering to produce 3D segmentations in anisotropic images. Comparison against other methods on experimental and synthetic datasets show that our method is more accurate (5-8% higher F1 score) and more robust across a range of baseline cell signals and image noise levels (6-17% higher F1 score). Further DL method is 3.7 times faster than previous method. Second, whole-brain imaging in freely moving worms is currently not widespread because of the requirement of custom designed microscopes with low-magnification behavior tracking and high-magnification fluorescence imaging channels. We developed and optimized a fast DL framework (30-644 times smaller model size and 5-8 times faster than previous methods) to directly predict the worm pose (skeleton) from fluorescence channels. Fast inference of pose using only fluorescence channel enables worm-tracking thus eliminating the need of separate behavior channel. We show that predicted worm pose can be used for behavior analysis and cell-tracking in videos. Further, eliminating the need of custom microscopes will enable more labs to do whole-brain imaging in freely moving animals. Third, we developed a DL framework for restoring low signal-to-noise ratio (SNR) fluorescence images (acquired at low laser power/low exposure time) to high SNR images. Low laser power imaging eliminates photo-bleaching of fluorophores, light damage to worms and enables long-term neuron activity imaging across days. Image restoration can be performed on both GCaMP and RFP channels. We show that restored images provide cleaner calcium signals compared to traditional de-noising methods (13-30% smaller mean-absolute error compared to clean trace). Additionally, restored images also improve cell detection, tracking and identity annotation tasks. Methods in our toolbox can be easily adapted for similar tasks in other organisms.

Guisnet, Aurelie et al. (2021) International Worm Meeting "A deep learning approach to calcium imaging analysis"

Rivest, Maxime, Guisnet, Aurelie, Hendricks, Michael

[International Worm Meeting, 2021]

Analysis of calcium imaging recordings is tedious, repetitive and time consuming. In this new project, we propose to develop a machine learning-based automated tool for the analysis of recordings from C. elegans neurons, thereby reducing noise, time loss and experimenter bias. We are specifically training our model to segment time-lapse fluorescence recordings of the RIA interneuron in semi-restrained animals. Our tool can segment animals and track their head movements as well as identify the three compartments of the RIA neurite. This prototype tool demonstrates the potential of deep learning to accelerate and improve data acquisition from time-lapse fluorescence recordings and other imaging data.

Manoharan, Arun Prasad et al. (2009) International Worm Meeting "small RNA profiling in the C. elegans germline and germ cells."

Hirst, Martin, Khivansara, Vishal, Manoharan, Arun Prasad, Chu, Diana, Kim, John, Fitzpatrick, Colin, Marra, Marco, Han, Ting

[International Worm Meeting, 2009]

To identify classes of small RNAs expressed in the germline and germ cells, we performed a genome-wide analysis of the small RNA transcriptome in C. elegans. Small RNAs play central roles in regulating germline development. Mutations affecting various small RNA pathways are frequently associated with the loss of fertility. To uncover small RNAs enriched in the germline and germ cells, we sequenced the small RNAs expressed in N2 worms, the glp-4(bn2) temperature-sensitive germline mutant, purified sperm from him-8 and purified oocytes from fer-1, and in N2 embryos. By high-throughput deep sequencing, using the Solexa (Illumina) and 454 (Roche) platforms, we generated over 14 million sequence reads that map perfectly to the C. elegans genome. Comparative analysis allowed us to determine enrichment of particular small RNAs to different cell types. For example, comparing the expression of small RNAs in N2 vs. glp-4 identified 25 miRNAs that were enriched 5-fold or higher in the germline and 19 miRNAs that were enriched in the soma. Comparisons between oocyte and sperm samples identified 49 miRNAs that were enriched 5-fold or higher in oocytes but only 3 miRNAs that were enriched in sperm. Computational analysis indicates that the putative miRNA targets are also enriched in these particular tissues or cell types. In addition to comparative analysis of known classes of small RNAs, we have identified 70 potentially novel microRNAs as well as additional germline-expressed 21U RNAs (1-4), many of which we validated by northern blot analysis and a PCR-amplified sequencing method. Finally, deep sequencing revealed a class of endogenous siRNAs, the 26G RNAs, which are enriched in sperm, oocytes, and embryos (discussed in a separate abstract.). We are currently investigating a select number of small RNAs for further analysis. Our deep sequencing of the small RNA transcriptome may provide a useful resource for future studies of gene regulation mediated by different classes of small RNAs in the germline. 1.Ruby, J.G. et al., Cell (2006) 127:1193-1207. 2.Batista, P.J. et al., Mol. Cell (2008) 31: 67-78. 3.Das, P.P. et al., Mol Cell (2008) 31: 79-90. 4.Wang, G. and Reinke, V., Curr. Biol. (2008) 18: 861-867.

Papp, Andrew et al. (2017) International Worm Meeting "The Relative significance of different fluorophores to Molecular Genetics research."

Savehshemshaki, Pegah, Papp, Andrew

[International Worm Meeting, 2017]

Background Various fluorophores are used to label molecules of interest to determine the presence, location, and timing of gene expression, and gene-gene interactions, as well as neuronal activity. This labeling can be accomplished through antibody binding, the creation of transgenic organisms with fluorescent fusion proteins or reporter genes, or ion-responsive fluorescent proteins. To find out the relative prevalence of various fluorophores in molecular genetics research is important in that it can help researchers choose fluorescent markers most useful to others and to buy equipment most likely to be useful; the data can also be useful to equipment designers so as to focus efforts on lowering the cost of detecting the most common fluorophores. To this end, an online survey ranking the relative use of various fluorophores was posted to the C. elegans and Drosophila bionet groups in November 2016. Discussion The data show that green fluorescence is used most often. This could be due to its ease of detection with equipment already present in many labs to detect FITC antibodies, generally high signal levels, and the fact that Green Fluorescent Protein was the first gene with a fluorescent protein product generally available to the scientific community after the publication of "Green fluorescent protein as a marker for gene expression" by Chalfie et al., 1994 in Science. 1994 Feb 11;263(5148):802-5. Reddish fluorophores can be divided into two groups based on their excitation and emission spectra. One group is excited by greenish light and fluoresces orangish-red light (such as dsRed and TRITC) while the second group is excited by yellowish light and fluoresces deep red (such as mCherry and Texas Red). Our results show that, while not as commonly used as green fluorescence, deep red fluorescence is used more often than orange-red fluorescence. This may be because, in double fluorescence labeling experiments, it is easier to create two distinct fluorescence channels using the redder fluorescence. Unlike the dsRed's orange-red fluorescence, mCherry's deep red is not excited significantly by the blue light used to excite green fluorescence. Our existing data will be presented in graphical form, and a live continuation of the survey will be conducted at our poster at the C. elegans Meeting Poster Session, with final results being published in the Worm Breeder's Gazette. We will also compile and publish a list of favorite fluorescence marker strains.

Gutwein, Michelle et al. (2013) International Worm Meeting "3' End Profiling of Gametogenesis in C. elegans Using RNA-Seq."

Gutwein, Michelle, Mecenas, Desirea, Piano, Fabio, Scheid, Paul, Ahmed, Rina, Gunsalus, Kris

[International Worm Meeting, 2013]

Post-transcriptional regulation of gene expression is largely mediated through sequence elements in the 3'UTR of protein-coding genes. One of our major interests is to understand post-transcriptional regulatory mechanisms during development. The C. elegans germline provides an excellent model to study post-transcriptional regulation because it is the primary determinant of gene expression in this organ (Merritt et al., Curr Biol 2008). We would like to characterize differences in 3'UTR isoform usage throughout gametogenesis by profiling 3'UTR ends in mitotic and meiotic regions of the gonad as well as in oocytes as a first step toward analyzing the contribution of putative regulatory elements in different regions of 3'UTRs. Next-generation sequencing has been useful to provide a deep sampling of transcriptional landscapes. However, transcript 3' termini are under-represented using standard RNA-seq library preparation protocols, rendering targeted analysis challenging. A number of specialized protocols to characterize the exact position of 3'end cleavage and polyadenylation have been developed, but they generally require larger sample sizes than are practical to extract from very specific tissues or cells in model organisms like C. elegans. Our aim is to develop new protocols that optimize 3'UTR endpoint analysis using small sample sizes for tissue-specific profiling with RNA-seq analysis. We have designed and tested a library preparation protocol for linear amplification and 3' end capture followed by deep sequencing on the Illumina HiSeq. We perform paired-end sequencing using a non-standard protocol designed specifically to avoid issues with sequencing the low-complexity polyA tail of transcripts. Here we present our progress in using this protocol with samples of RNA extracted from whole male and hermaphrodite N2 gonads, as well as dissected mitotic and meiotic regions and oocytes from hermaphrodite gonads in order to characterize 3'UTR diversity during germline development.

Sapir, Amir et al. (2011) International Worm Meeting "Unveiling the unique biology of nematodes living in a cold methane seep on the ocean floor and their symbiosis with chemosynthetic bacteria."

Mundo-Ocampo, Manuel, Sapir, Amir, Orphan, Victoria J., Sternberg, Paul W., Baldwin, James G., Dillman, Adler R.

[International Worm Meeting, 2011]

The complex life of microbes in deep sea chemosynthetic environments is being actively deciphered with a focus on microbes' ecology and metabolism. In contrast, the biology of several nematode species that were reported to live in these habitats remains largely elusive. To start addressing questions of nematodes ecology, metabolism, and symbiosis with microbes in chemosynthetic environments we sampled and sorted worms from Hydrate Ridge, a cold methane seep off the Oregon coast 774 meters below the sea surface. This niche is characterized by low oxygen levels (anoxic/ microoxic), low temperature, and high concentration of hydrogen sulfide. Chemotrophic microorganisms drive primary production in this deep-sea ecosystem, deriving energy through sulfate-dependent methane oxidation or sulfide-oxidation. Stable isotopic analyses suggest that worms and other metazoans in this niche rely on these microbes as a food source. A molecular survey of nematodes from this seep site revealed a surprising level of diversity, representing a number of understudied phylogenetic clades. In contrast to many terrestrial free-living nematodes that are found in the wild primarily as dauers, the majority of nematodes identified in the samples were reproducing adults. This may suggest that at the time of sampling food was not the limiting factor. Combining DAPI staining with light and scanning electron microscopy we discovered a complex nematode-bacteria relationship including the distribution of external and internal symbionts: The worm's hypodermis is covered with microbes and in two different worm species we identified two morphologically different microbes in the body cavity suggesting species-specific interactions between nematodes and microbes. Preliminary profiling of the external and internal microbes in selected species identified the associated microbes as bacteria. We report the characterization of symbiont diversity with respect to nematode hosts as a first step toward understanding worm-microbe symbiosis and worms' adaptation to extreme chemosynthetic environments.

Sonoda, Satoru et al. (2013) International Worm Meeting "Isolating genes for temperature experience-dependent cold tolerance."

Uehara, Yushuke, Kinoshita, Yukari, Ohta, Akane, Endo, Mikiko, Kuhara, Atsushi, Sonoda, Satoru, Furukawa, Shoko

[International Worm Meeting, 2013]

We are utilizing temperature experience-dependent cold tolerance as a model for studying temperature sensation and habituation. After cultivation at 20 deg C, wild-type were destroyed by cold stimuli. In contrast, after cultivation at 15 deg C, most of animals can survive. To isolate genes involved in the cold tolerance, we are using four approaches, (1) DNA microarray, (2) Natural variation, (3) Artificial evolution and (4) EMS-mutagenesis. (1) We tested cold tolerance of mutants defective in genes isolated from DNA microarray analysis (Ajilent array). Several genes such as protein protease PP1 and laminin are involved in cold tolerance. Since PP1/GSP-3 is involved in sperm development and motility, and mutants impairing sperm genes showed abnormal cold tolerance. We are now investigating the relationship between sperm genes for cold tolerance and known-cold tolerance signaling pathway, such as insulin signaling and G protein-coupled temperature signaling in ASJ neuron. (2) Natural C. elegans isolated from various area showed variety of cold tolerance. Responsible gene for natural variation between Bristol N2 and California CB4854 are genetically mapped on X-chromosome. Using deep DNA sequencer and SNP analysis, candidates of responsible genes are narrowed down to ~20 genes. (3) C. elegans has strong advantage for artificial evolution analysis, since life cycle is short and strains can be preserved at -80 deg C. We are maintaining wild-type at 15 or 23 deg C for gradual accumulation of mutations. So far, 87 generations are frozen, and we found that cold tolerance was notably changed at 61 generation. We are planning to decode whole genome by using deep DNA sequencer. (4) Through 2000 genomes screen by using EMS, we isolated 10 cold tolerance mutations. One of these has been mapped on X-chromosome.