Automation of C. elegans lifespan measurement

The prospects of automation in drug discovery research using silkworms

We have established several models of infectious diseases in silkworms to explore disease-causing mechanisms and identify new antimicrobial substances. These models involve injecting laboratory-cultured pathogens into silkworms and monitoring their survival over a period of days. The use of silkworms is advantageous because they are cost-effective and raise fewer ethical concerns than mammalian subjects, allowing for larger experimental group sizes. To capitalize on these benefits, there is a growing importance in mechanizing and automating the experimental processes that currently require manual labor. This paper discusses the future of laboratory automation, specifically through the mechanization and automation of silkworm-based experimental procedures.

The role of Caenorhabditis elegans in the discovery of natural products for healthy aging

Covering: 2012 to 2023The human population is aging. Thus, the greatest risk factor for numerous diseases, such as diabetes, cancer and neurodegenerative disorders, is increasing worldwide. Age-related diseases do not typically occur in isolation, but as a result of multi-factorial causes, which in turn require holistic approaches to identify and decipher the mode of action of potential remedies. With the advent of C. elegans as the primary model organism for aging, researchers now have a powerful in vivo tool for identifying and studying agents that effect lifespan and health span. Natural products have been focal research subjects in this respect. This review article covers key developments of the last decade (2012-2023) that have led to the discovery of natural products with healthy aging properties in C. elegans. We (i) discuss the state of knowledge on the effects of natural products on worm aging including methods, assays and involved pathways; (ii) analyze the literature on natural compounds in terms of their molecular properties and the translatability of effects on mammals; (iii) examine the literature on multi-component mixtures with special attention to the studied organisms, extraction methods and efforts regarding the characterization of their chemical composition and their bioactive components. (iv) We further propose to combine small in vivo model organisms such as C. elegans and sophisticated analytical approaches ("wormomics") to guide the way to dissect complex natural products with anti-aging properties.

Aging, longevity, and the role of environmental stressors: a focus on wildfire smoke and air quality

Aging is a complex biological process involving multiple interacting mechanisms and is being increasingly linked to environmental exposures such as wildfire smoke. In this review, we detail the hallmarks of aging, emphasizing the role of telomere attrition, cellular senescence, epigenetic alterations, proteostasis, genomic instability, and mitochondrial dysfunction, while also exploring integrative hallmarks - altered intercellular communication and stem cell exhaustion. Within each hallmark of aging, our review explores how environmental disasters like wildfires, and their resultant inhaled toxicants, interact with these aging mechanisms. The intersection between aging and environmental exposures, especially high-concentration insults from wildfires, remains under-studied. Preliminary evidence, from our group and others, suggests that inhaled wildfire smoke can accelerate markers of neurological aging and reduce learning capabilities. This is likely mediated by the augmentation of circulatory factors that compromise vascular and blood-brain barrier integrity, induce chronic neuroinflammation, and promote age-associated proteinopathy-related outcomes. Moreover, wildfire smoke may induce a reduced metabolic, senescent cellular phenotype. Future interventions could potentially leverage combined anti-inflammatory and NAD + boosting compounds to counter these effects. This review underscores the critical need to study the intricate interplay between environmental factors and the biological mechanisms of aging to pave the way for effective interventions.

Automation of Caenorhabditis elegans lifespan assay using a simplified domain synthetic image-based neural network training strategy

Performing lifespan assays with Caenorhabditis elegans (C. elegans) nematodes manually is a time consuming and laborious task. Therefore, automation is necessary to increase productivity. In this paper, we propose a method to automate the counting of live C. elegans using deep learning. The survival curves of the experiment are obtained using a sequence formed by an image taken on each day of the assay. Solving this problem would require a very large labeled dataset; thus, to facilitate its generation, we propose a simplified image-based strategy. This simplification consists of transforming the real images of the nematodes in the Petri dish to a synthetic image, in which circular blobs are drawn on a constant background to mark the position of the C. elegans. To apply this simplification method, it is divided into two steps. First, a Faster R-CNN network detects the C. elegans, allowing its transformation into a synthetic image. Second, using the simplified image sequence as input, a regression neural network is in charge of predicting the count of live nematodes on each day of the experiment. In this way, the counting network was trained using a simple simulator, avoiding labeling a very large real dataset or developing a realistic simulator. Results showed that the differences between the curves obtained by the proposed method and the manual curves are not statistically significant for either short-lived N2 (p-value log rank test 0.45) or long-lived daf-2 (p-value log rank test 0.83) strains.

Surface acoustic wave microfluidics for repetitive and reversible temporary immobilization of C. elegans

Caenorhabditis elegans is an important genetic model for neuroscience studies, used for analyses of how genes control connectivity, neuronal function, and behavior. To date, however, most studies of neuronal function in C. elegans are incapable of obtaining microscopy imaging with subcellular resolution and behavior analysis in the same set of animals. This constraint stems from the immobilization requirement for high-resolution imaging that is incompatible with behavioral analysis using conventional immobilization techniques. Here, we present a novel microfluidic device that uses surface acoustic waves (SAW) as a non-contact method to temporarily immobilize worms for a short period (30 seconds). We optimize the SAW based protocol for rapid switching between free-swimming and immobilized states, facilitating non-invasive analysis of swimming behavior as well as high-resolution synaptic imaging in the same animal. We find that the coupling of heat and acoustic pressure play a key role in the immobilization process. We introduce a proof-of-concept longitudinal study, illustrating that the device enables repeated imaging of fluorescently tagged synaptic receptors in command interneurons and analysis of swimming behavior in the same animals for three days. This longitudinal approach provides the first correlative analysis of synaptic glutamatergic receptors and swimming behavior in aging animals. We anticipate that this device will enable further longitudinal analysis of animal motility and subcellular morphological changes during development and aging in C. elegans.

Applying C. elegans to the Industrial Drug Discovery Process to Slow Aging

The increase in our molecular understanding of the biology of aging, coupled with a recent surge in investment, has led to the formation of several companies developing pharmaceuticals to slow aging. Research using the tiny nematode worm Caenorhabditis elegans was the first to show that mutations in single genes can extend lifespan, and subsequent research has shown that this model organism is uniquely suited to testing interventions to slow aging. Yet, with a few notable exceptions, C. elegans is not in the standard toolkit of longevity companies. Here we discuss the paths to overcome the barriers to using C. elegans in industrial drug discovery. We address the predictive power of C. elegans for human aging, how C. elegans research can be applied to specific challenges in the typical drug discovery pipeline, and how standardised and quantitative assays will help C. elegans fulfil its potential in the biotech and pharmaceutical industry. We argue that correct application of this model and its knowledge base will significantly accelerate progress to slow human aging.

Explaining inter-lab variance in C. elegans N2 lifespan: Making a case for standardized reporting to enhance reproducibility

The nematode Caenorhabditis elegans is a powerful model organism for studying cell development, apoptosis, neuronal circuits, and aging. The isolate N2 is recognized by the C. elegans community as the reference wild-type strain. Interestingly, the lifespan of presumably isogenic C. elegans N2 worms-even when grown under comparable conditions-varies significantly amongst distinct laboratories. This hinders the inter-laboratory comparability of C. elegans lifespan data and raises questions regarding data interpretation and reproducibility. Here, we hypothesized slight alterations in experimental design and worm handling could explain the observed discrepancies. To test this hypothesis, we collected and assessed data from over 1000 published C. elegans N2 lifespan assays as well as corresponding methodological meta-data. We find that mean N2 lifespans range from approximately 7 days to upwards of 35 days, despite laboratories disclosing seemingly comparable experimental conditions. We further demonstrate that, in addition to temperature, the use of the chemical sterilizer 5-fluoro-2'-deoxyuridine (FUDR) may change N2 lifespan. Additionally, we observed differences in average N2 lifespan from experiments originating from distinct geographic locations, indicating a potential effect of location-specific factors on experimental outcomes. Taken as a whole, our work indicates the sum of many small, rather than a few critical, differences in experimental conditions may account for the observed variance in N2 lifespan. We also find that the absence of standardized experimental methods and the insufficient disclosure of experiment details in the peer-reviewed literature limits the inter-lab comparability of published results. We thus propose the establishment of a succinct reporting standard for C. elegans lifespan experiments to increase the reliability and reproducibility, and thus scientific value, of these studies.

Towards Lifespan Automation for Caenorhabditis elegans Based on Deep Learning: Analysing Convolutional and Recurrent Neural Networks for Dead or Live Classification

The automation of lifespan assays with C. elegans in standard Petri dishes is a challenging problem because there are several problems hindering detection such as occlusions at the plate edges, dirt accumulation, and worm aggregations. Moreover, determining whether a worm is alive or dead can be complex as they barely move during the last few days of their lives. This paper proposes a method combining traditional computer vision techniques with a live/dead C. elegans classifier based on convolutional and recurrent neural networks from low-resolution image sequences. In addition to proposing a new method to automate lifespan, the use of data augmentation techniques is proposed to train the network in the absence of large numbers of samples. The proposed method achieved small error rates (3.54% ± 1.30% per plate) with respect to the manual curve, demonstrating its feasibility.

Intrapopulation analysis of longitudinal lifespan in Caenorhabditis elegans identifies W09D10.4 as a novel AMPK-associated healthspan shortening factor

Caenorhabditis elegans is a model organism widely used for longevity studies. Current advances have been made in the methods that allow automated monitoring of C. elegans behavior. However, ordinary manual assays as well as automated methods have yet to achieve qualitative whole-life analysis of C. elegans longevity based on intrapopulation variation. Here, we utilized live-cell analysis system to determine the parameters of nematode lifespans. Image-based superposition method enabled to determine not only frailty in worms, but also to measure individual and longitudinal lifespan, healthspan, and frailspan. Notably, k-means clustering via principal component analysis revealed four clusters with distinct longevity patterns in wild-type C. elegans. Physiological relevance of clustering was confirmed by assays with pharmacological and/or genetic manipulation of AMP-activated protein kinase (AMPK), a crucial regulator of healthspan. Finally, we focused on W09D10.4 among the possible regulators extracted by integrative expression analysis with existing data sets. Importantly, W09D10.4 knockdown increased the high-healthspan populations only in the presence of AMPK, suggesting that W09D10.4 is a novel AMPK-associated healthspan shortening factor in C. elegans. Overall, the study establishes a novel platform of longitudinal lifespan in C. elegans, which is user-friendly, and may be a useful pharmacological tool to identify healthspan modulatory factors.