Abstract

C. elegans is an established model organism for studying genetic and drug effects on aging, many of which are conserved in humans. It is also an important model for basic research, and C. elegans pathologies is a new emerging field. Here we develop a proof-of-principal convolutional neural network-based platform to segment C. elegans and extract features that might be useful for lifespan prediction. We use a dataset of 734 worms tracked throughout their lifespan and classify worms into long-lived and short-lived. We designed WormNet - a convolutional neural network (CNN) to predict the worm lifespan class based on young adult images (day 1 – day 3 old adults) and showed that WormNet, as well as, InceptionV3 CNN can successfully classify lifespan. Based on U-Net architecture we develop HydraNet CNNs which allow segmenting worms accurately into anterior, mid-body and posterior parts. We combine HydraNet segmentation, WormNet prediction and the class activation map approach to determine the segments most important for lifespan classification. Such a tandem segmentation-classification approach shows the posterior part of the worm might be more important for classifying long-lived worms. Our approach can be useful for the acceleration of anti-aging drug discovery and for studying C. elegans pathologies.

Highlights

  • The nematode Caenorhabditis elegans (C. elegans) is an established model for studying various interventions into the aging process, which allowed to find numerous genes and drugs interfering with aging. 5 out of 7 Tier 1 and 4 out of 6 Tier 2 anti-aging drugs considered for human trials extend lifespan in the C. elegans model

  • Studying pathologies in C. elegans might help to get a better understanding of the aging process, as well as, the mechanisms and effects of antiaging drugs

  • Our results suggested that the model performance is predominantly attributed to the C. elegans morphology rather than the background of the images

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Summary

Introduction

The nematode Caenorhabditis elegans (C. elegans) is an established model for studying various interventions into the aging process, which allowed to find numerous genes and drugs interfering with aging. 5 out of 7 Tier 1 and 4 out of 6 Tier 2 anti-aging drugs considered for human trials extend lifespan in the C. elegans model. The nematode Caenorhabditis elegans (C. elegans) is an established model for studying various interventions into the aging process, which allowed to find numerous genes and drugs interfering with aging. 5 out of 7 Tier 1 and 4 out of 6 Tier 2 anti-aging drugs considered for human trials extend lifespan in the C. elegans model. Several pathologies including gut atrophy, uterine tumours and pharyngeal infection were described recently [4,5,6]. In this light, discovering new C. elegans pathologies, determining lifespan, is becoming an important challenge. Studying pathologies in C. elegans might help to get a better understanding of the aging process, as well as, the mechanisms and effects of antiaging drugs

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