Zetka M-C et al. (1993) Worm Breeder's Gazette "Mapping of the rec-1 Mutation"

Rose AM, Zetka M-C

[Worm Breeder's Gazette, 1993]

MAPPING OF THE rec-1 MUTATION Monique-Claire Zetka and Ann M. Rose, Dept. of Medical Genetics, 6174 University Blvd., University of British Columbia, Vancouver, B.C., V6T lZ3.

Haesemeyer M et al. (2019) Neuron "Convergent Temperature Representations in Artificial and Biological Neural Networks."

Engert F, Haesemeyer M, Schier AF

[Neuron, 2019]

Discoveries in biological neural networks (BNNs) shaped artificial neural networks (ANNs) and computational parallels between ANNs and BNNs have recently been discovered. However, it is unclear to what extent discoveries in ANNs can give insight into BNN function. Here, we designed and trained an ANN to perform heat gradient navigation and found striking similarities in computation and heat representation to a known zebrafish BNN. This included shared ON- and OFF-type representations of absolute temperature and rates of change. Importantly, ANN function critically relied on zebrafish-like units. We furthermore used the accessibility of the ANN to discover anew temperature-responsive cell type in the zebrafish cerebellum. Finally, constraining the ANN by the C.elegans motor repertoire retuned sensory representations indicating that our approach generalizes. Together, these results emphasize convergence of ANNs and BNNs on stereotypical representations and that ANNs form a powerful tool to understand their biological counterparts.

Bargmann C (2024) Neuron "Cori Bargmann."

Bargmann C

[Neuron, 2024]

In an interview with Neuron, Cori Bargmann discusses C. elegans as a model organism, the importance of considering the animal's own world (thinking like a worm), choosing a scientific problem, and her experience as head of science at the Chan Zuckerberg Initiative and co-chair of the BRAIN Initiative.

A H Jay Burr et al. (2001) International C. elegans Meeting "Light-increased reversal frequency and spontaneous reversal frequency are affected by starvation."

A H Jay Burr, Ann Chan, Wendell Challenger

[International C. elegans Meeting, 2001]

C elegans was shown previously to reverse direction in response to light (Burr 1985). In that study, 40-80% increases in reversal frequency over the background level varied with light intensity and wavelength in a normal way and were shown not to be due to radiant heating. Because large sample sizes are needed in order to detect small increases on top of the fluctuating frequency of spontaneous reversals, we have developed a computer automated tracking system that makes experimentation possible in a reasonable length of time. Under continuous near-infrared illumination, video images are digitized once each second and processed to find the new coordinates of up to 23 worms. Another program identifies reversals from the coordinates along the track. These are counted during a 10 s light period (1.6 x10 4 uW cm -2 blue-white broadband light) and a preceding 10 s dark period in each 40 s measurement cycle. There are 5 cycles per 200 s run. The number of reversals per 10 s measurement period, averaged over all worms and cycles during a run, counts as one independent measurement. Data are analyzed as a generalized randomized complete block design using the Proc Mixed procedure of SAS version 8. For detecting the effect of light, the difference in reversal frequency between the paired light and dark periods is analyzed in the same way. A new sample of worms was used for each run. About 30 synchronous six day-old, well-fed worms were washed off an OP50 culture plate and sedimented twice through behavior buffer (5.5 mM Tris + 34 mM NaCl). The worms were transferred in a drop of buffer to the edge of a 50-mm behavior plate and the plate was rotated to distribute the worms around the edge. The behavior plates were prepared by making 1.8% agar in 90% behavior buffer then drying to 90% of poured weight. Just before using, about 100 uL distilled water was distributed around the edge and allowed to soak in. The resulting lower osmolarity at the agar perimeter discouraged the worms from crawling near the edge. Worms were allowed to crawl into the 22x28 mm field of view and were tracked within 30-50 min of removal from the food. All procedures were carried out at 19 C. Sensitivity of the system under actual conditions was estimated by simulation, starting with data from an experiment with fed worms during which the light beam was blocked. Reversals were added to the data during the 'light' periods at frequencies of 0.01 to 0.10 per 10 s period (perP), and the data were reanalyzed. The increase in reversal frequency became significant at 0.050 perP (P = 0.037, n = 21 runs), a 45% increase over the background (dark period) frequency. A greater sensitivity would be expected at higher sample sizes. In all our experiments with well-fed worms, light had no significant effect on reversal frequency. To investigate the influence of starvation, we pooled worms from several food plates and put half on a food-free plate and half on a fresh food plate. After a starvation period, the fed and starved worms were tested in alternate runs. Light increased reversal frequency significantly in worms starved 20 h (+0.040 perP, +62%, P=0.049, n=51), but not significantly in worms starved 6 h (+0.013 perP, +12%, P = 0.4, n = 39). In both experiments, light had no significant effect on the fed controls (-0.023 perP, -15%, P = 0.2, n = 58 and -0.015 perP, -9%, P = 0.4, n = 42). In addition to being more responsive to light, starved worms had a significantly lower background (dark period) frequency. For the 0 h, 6 h and 20 h starved worms, average dark frequency (+/- SE) was 0.15 (0.013) perP, 0.11 (0.013) perP and 0.064 (0.012) perP, respectively. Thus, both background reversal frequency and responsiveness to light appear to be affected by starvation. In the previous study in which light responses were observed (Burr 1985), the worms may inadvertently have been starved.

Wang X et al. (2024) Adv Sci (Weinh) "An Artificial Neural Network for Image Classification Inspired by the Aversive Olfactory Learning Neural Circuit in Caenorhabditis elegans."

Zhang K, Di Z, Liu C, Wang X, Zhao M, Liu H

[Adv Sci (Weinh), 2024]

This study introduces an artificial neural network (ANN) for image classification task, inspired by the aversive olfactory learning neural circuit in Caenorhabditis elegans (C. elegans). Although artificial neural networks (ANNs) have demonstrated remarkable performance in various tasks, they still encounter challenges including excessive parameterization, high training costs and limited generalization capabilities, etc. C. elegans, boasting a simple nervous system consisting of merely 302 neurons, is capable of exhibiting complex behaviors such as aversive olfactory learning. This research pinpoints key neural circuit related to aversive olfactory learning in C. elegans by means of behavioral experiment and high-throughput RNA sequencing, and then translates it into an architecture of ANN for image classification. Furthermore, other ANNs for image classification with different architectures are constructed for comparative performance analysis to underscore the advantages of the bio-inspired designed architecture. The results show that the ANN inspired by the aversive olfactory learning neural circuit in C. elegans attains higher accuracy, greater consistency and faster convergence rate in the image classification task, particularly when dealing with more complex classification challenges. This study not only demonstrates the potential of bio-inspired design in improving the capabilities of ANNs but also offers a novel perspective and methodology for future ANNs design.

(2019) Development "The people behind the papers - Daniel Osorio, Elaine Chan, Joana Saramago and Ana Carvalho."

[Development, 2019]

Animal cytokinesis is driven by an actomyosin ring that assembles at the cell equator and constricts to physically separate the two daughters. Although myosin is known to be essential for cytokinesis in multiple systems, whether this requirement reflects its motor or actin crosslinking activities has recently been a matter of contention. A new paper in Development now addresses this problem using the first divisions of the <i>Caenorhabditis elegans</i> embryo as a model. We caught up with the paper's three first authors Daniel Osorio, Elaine Chan and Joana Saramago, and their supervisor Ana Carvalho, Principal Investigator at the University of Porto's i3S consortium, to find out more about the story.

Avery L (1995) Worm Breeder's Gazette "Effects of Conus venoms on the pharynx"

Avery L

[Worm Breeder's Gazette, 1995]

Cone snails are predatory snails. They harpoon their prey, which may be small fish, marine worms, or other snails, then inject a paralyzing venom through the hollow harpoon (Olivera et al, Science 249: 257). The venom is a complex mixture of tiny peptide toxins, different in each species. Several of these toxins have been shown to act on cell-surface molecules important for nervous system function such as the N-type Ca++ channel or the voltage-gated Na+ channel (Gray et al, Ann Rev Biochem 57: 665).

Park C et al. (2023) Exp Neurobiol "Caenorhabditis elegans Connectomes of both Sexes as Image Classifiers."

Kim JS, Park C

[Exp Neurobiol, 2023]

Connectome, the complete wiring diagram of the nervous system of an organism, is the biological substrate of the mind. While biological neural networks are crucial to the understanding of neural computation mechanisms, recent artificial neural networks (ANNs) have been developed independently from the study of real neural networks. Computational scientists are searching for various ANN architectures to improve machine learning since the architectures are associated with the accuracy of ANNs. A recent study used the hermaphrodite <i>Caenorhabditis elegans</i> (<i>C. elegans</i>) connectome for image classification tasks, where the edge directions were changed to construct a directed acyclic graph (DAG). In this study, we used the whole-animal connectomes of <i>C. elegans</i> hermaphrodite and male to construct a DAG that preserves the chief information flow in the connectomes and trained them for image classification of MNIST and fashion-MNIST datasets. The connectome-inspired neural networks exhibited over 99.5% and 92.6% of accuracy for MNIST and fashion-MNIST datasets, respectively, which increased from the previous study. Together, we conclude that realistic biological neural networks provide the basis of a plausible ANN architecture. This study suggests that biological networks can provide new inspiration to improve artificial intelligences (AIs).

Cirillo, L. et al. (2015) International Worm Meeting "Coordinating Cdk1 and Plk1 activation for mitotic entry in early C. elegans embryos and human cells."

Cirillo, L., Van Hove, L., Gotta, M., Martino, L., Schwager, F., Panbianco, C., Santamaria, A., Thomas, Y., Pindard, L.

[International Worm Meeting, 2015]

Entry into mitosis is regulated by several kinases including Cdk1, Aurora A and Plk1. However, how the activity of these kinases is coordinated in space and time is not fully understood. Our laboratories have recently shown that SPAT-1, an activator of Plk1, is phosphorylated by Cdk-1 at several sites in C. elegans. Our in vivo and in vitro data revealed that phosphorylation of the N-terminal sites is crucial to promote the interaction with PLK-1 and its activation. Together, our results suggest the existence of a positive feedback loop that connects CDK-1 and PLK-1 via SPAT-1 and ensures a robust control of cell division timing during embryonic development.The human ortholog of SPAT-1, Bora, regulates several aspects of mitosis (Bruinsma et al. 2014, Chan et al 2008, Macurek et al. 2008, Seki et al. 2008). Although phosphorylation of Bora is not strictly required to activate Plk1 (Seki et al. 2008, our unpublished data) we find that Cdk1 phosphorylation of Bora greatly increases Plk1 activation in vitro. We have mapped the Cdk1 phosphorylation sites of Bora. Based on the results obtained in C. elegans, we have mutated a number of N-terminal sites and found that Bora ability to activate Plk1 is greatly reduced in vitro. We are currently testing the function of these sites in human cells by monitoring these mutants in vivo. Our data will help to shed light on the activation mechanisms of Plk1 by Bora. Since Plk1 is overexpressed in many cancers, understanding the precise mechanisms of activation of this kinase will help the design of anti-cancer drugs.References:Bruinsma W. et al. J Cell Sci. 2014; Chan EH. et al. Chromosoma. 2008; Macurek L. et al. Nature. 2008; Seki A. et al. Science. 2008.

Saleel Raut et al. (2008) C.elegans Neuronal Development Meeting "HLH-3, a C. elegans Achaete/Scute protein, has a role in the axonal pathfinding of hermaphrodite-specific motor neuron (HSN) that is independent of UNC-40."

Saleel Raut, Aixa Alfonso

[C.elegans Neuronal Development Meeting, 2008]

The basic helix loop helix protein, HLH-3, is a member of the achaete/scute family in C. elegans hlh-3 mutants have an egg-laying defective (Egl) phenotype. We have shown (Doonan et al., 2008 submitted) that the mutant phenotype results from abnormal axonal pathfinding in hermaphrodite-specific motor neurons (HSNs) that fail to innervate the vulval muscles. The NETRIN/UNC-6 receptor UNC-40/DCC is necessary for the guidance of the HSN axons (Garriga et al.,1993; Chan et al., 1996; Gitai et al., 2003; Adler et al., 2006). We hypothesized that mutant animals are not uncoordinated (Unc). Currently we are looking at SYG-1, a receptor on HSN''s that binds with the guidepost signal SYG-2 for proper synapse formation (Shen et al., 2004), as a possible target of HLH-3.