Biology subjects

Hendricks, M.

Publications and source records attributed to Hendricks, M..

7 recordsLinked to original sources

bioRxiv2025

The impact of rearing environment on C. elegans: Phenotypic, transcriptomic and intergenerational responses to 3D enriched habitats

Environmental context profoundly influences organismal biology, yet laboratory studies often rely on simplified conditions that may not fully capture natural phenotypic repertoire. This exploratory study investigated how rearing environment affects various aspects of Caenorhabditis elegans biology by comparing worms cultured in three-dimensional decellularized fruit tissue scaffolds with those raised on standard two-dimensional agar plates. While fat content and feeding rate remained stable across conditions, other life history traits demonstrated varying degrees of plasticity in response to environmental context. We observed that scaffold-grown worms exhibited reduced body size, altered reproductive strategies, and mild enhancements in stress resistance, burrowing ability, swimming kinematics and exploratory behavior. RNA sequencing revealed distinct transcriptional profiles between scaffold-grown and agar-grown worms, with most changes arising within one generation. Some traits showed evidence of intergenerational inheritance. Our findings highlight the sensitivity of C. elegans biology to rearing conditions and underscore the importance of considering environmental context in interpreting laboratory results. This work sets the foundation for future research into the mechanisms underlying environmental adaptation and phenotypic plasticity in model organisms. Summary statementThis study reveals how simple changes in environmental complexity can alter the development, behavior, and gene expression of laboratory animals.

animal behavior and cognition↗

bioRxiv2025

Large vision model framework for automated C. elegans analysis: From static morphometry to dynamic neural activity

Quantitative phenotyping of Caenorhabditis elegans is essential across numerous fields, yet data extraction remains a significant analytical bottleneck. Traditional segmentation methods, typically reliant on pixel-intensity thresholding, are highly sensitive to variations in imaging conditions and often fail in the presence of noise, overlaps, or uneven illumination. These failures necessitate meticulous experimental setups, expensive hardware, or extensive manual curation, which reduces throughput and introduces bias. Here, we introduce TWARDIS (Tools for Worm Automated Recognition & Dynamic Imaging System), a modular, Python-based analysis suite that leverages large foundation vision models, specifically the Segment Anything Models (SAM and SAM2) and a fine-tuned vision transformer classifier, to overcome these limitations. We demonstrate the versatility and robustness of our AI compound system across diverse modalities. For static morphological analysis, TWARDIS successfully resolved overlapping worms in noisy images without human intervention, showing a 0.999 correlation with manual segmentation. In behavioral assays (swimming and crawling), the pipeline enabled high-definition postural analysis even in low-resolution, wide-field recordings where the worm occupied only [~]0.25% of the field of view, accurately resolving complex postures without frame rejection. Finally, when applied to calcium imaging of semi-restricted animals, TWARDIS provided precise, frame-by-frame segmentation of neural compartments, reducing the artificial signal flattening common in traditional region-of-interest-based approaches and enabling the extraction of biologically accurate, absolute head positions. The systems hardware-scalable architecture and modular design ensure both current accessibility and future improvements without restructuring. By automating the most time-consuming aspects of image analysis, TWARDIS removes critical bottlenecks and tradeoffs in C. elegans research, enabling researchers to focus on biological questions rather than technical image processing challenges. Author SummaryThe small roundworm Caenorhabditis elegans is widely used by scientists to study fundamental biological questions, such as aging and how the brain works. A crucial part of this research involves analyzing images and videos to measure the worms shape, movement, and neural activity. However, extracting accurate data is a major challenge. Traditional software tools often fail if the lighting is uneven, the image is noisy, or worms overlap. This forces researchers to spend countless hours manually correcting errors or investing in expensive, specialized equipment. To overcome this bottleneck, we developed TWARDIS (Tools for Worm Automated Recognition & Dynamic Imaging System). Our system utilizes recent advances in Artificial Intelligence, harnessing powerful, generalized AI models to automatically and accurately identify the worms, even in challenging images. We demonstrated that TWARDIS reliably analyzes complex behaviors and neural activity without human intervention. Our approach removes the traditional trade-off between data quality and equipment cost, enabling high-precision analysis using simple setups. By automating the most tedious parts of image analysis, TWARDIS allows scientists to focus on biological discovery rather than technical hurdles.

neuroscience↗

bioRxiv2025

A novel epifluorescence microscope design and soft-ware package to record naturalistic behaviour and cell activity in freely moving Caenorhabditis elegans.

Understanding how neural circuits drive behavior requires imaging methods that capture cellular dynamics in freely moving animals. Here, we introduce Wormspy, a compact, flexible, and cost-effective microscope system paired with an open-source software package, specifically designed for high-magnification epifluorescence imaging in Caenorhabditis elegans. By integrating dual-channel fluorescence optics, off-the-shelf components, and a motorized stage, Wormspy enables simultaneous recording of neuronal activity and behavioral dynamics without restraining the animal. Our system incorporates both manual and automated tracking--including DeepLabCut-based feature extraction--to maintain precise centering of the subject, even during complex locomotor behaviors. We demonstrate the utility of Wormspy across multiple paradigms: quantifying body wall muscle calcium transients during locomotion, capturing rapid sensory-evoked responses in the polymodal ASH neuron during aversive stimuli, and resolving food-related activity in the AWCON neuron. Notably, Wormspy further distinguishes subcellular calcium events in the RIA axonal compartments that correlate with head bending kinematics. This versatile platform not only reproduces known phenotypes, such as altered gait in gar-3 mutants, but also uncovers nuanced sensorimotor correlations previously inaccessible with conventional methods. Wormspys modular design and open-source framework lower the technical and financial barriers to high-resolution, behaviorally relevant neural imaging. Our findings establish Wormspy as a robust tool for dissecting the neural underpinnings of behavior in freely moving organisms, with potential applications extending to other small model systems.

neuroscience↗

bioRxiv2018

Asymmetric adaptation reveals functional lateralization for graded versus discrete stimuli

Abstract 150 wordsAnimal navigation strategies depend on the nature of the environmental cues used. In the nematode Caenorhabditis elegans, navigation has been studied in the context of gradients of attractive or repellent stimuli as well is in response to acute aversive stimuli. We wanted to better understand how sensory responses to the same stimulus vary between graded and acute stimuli, and how this variation relates to behavioral responses. C. elegans has two salt-sensing neurons, ASEL and ASER, that show opposite responses to stepped changes in stimulus levels, however only ASER has been shown to play a prominent role in salt chemotaxis. We used pre-exposure to natural stimuli to manipulate the responsiveness of these neurons and tested their separate contributions to behavior. Our results suggest ASEL is specialized for responses to acute stimulus changes. We also found that ASER remains responsive to graded stimuli under conditions where it is unresponsive to large steps.

neuroscience↗

bioRxiv2018

Environmental programming of adult foraging behavior in C. elegans

Foraging strategies must be tuned to the availability and distribution of resources in the environment. This can occur over generations and lead to genetic differences in foraging behavior, or it can occur on shorter time scales within an individuals life span. Both genetic and experience-based strategies must be implemented by neural circuits that respond to environmental cues and track internal states, and the analysis of such circuits provides insight into the neural basis of complex decision making. In C. elegans, between-strain genetic differences and within-strain plasticity in foraging has been observed. Most individual changes in foraging are short-term, based on experience over several hours. Here, we tested if developmental experience could permanently alter foraging. We found that in wild strains that are normally highly exploratory, early-life starvation leads to \"cautious\" foraging behavior in which exploration is reduced. We characterize the behavioral bases for these strategies and identify changes in the dynamics of a locomotory circuit involved in navigation. Overall, we show that some C. elegans strains exhibit adaptive tuning of their foraging behavior based on early-life experience, and this is associated with changes in a core navigation circuit.

neuroscience↗

bioRxiv2018

A gate-and-switch model for head orientation behaviors in C. elegans

The nervous system seamlessly integrates perception and action. This ability is essential for stable representation of and appropriate responses to the external environment. How the sensorimotor integration underlying this ability occurs at the level of individual neurons is of keen interest. In Caenorhabditis elegans, RIA interneurons receive input from sensory pathways and have reciprocal connections with head motor neurons. Through separate physiological mechanisms, RIA simultaneously encodes both head orientation and sensory stimuli. Based on these observations, we proposed a model for how RIA may integrate these two signals to detect the spatial distribution of stimuli across head sweeps and generate directional head responses. Here, we show that blocking synaptic release from RIA disrupts head orientation behaviors in response to unilaterally presented stimuli. We found that sensory encoding in RIA is gated according to head orientation. This dependence on head orientation is independent of motor encoding in RIA, suggesting a second, posture-dependent pathway upstream of RIA. This gating mechanism may allow RIA to selectively attend to stimuli that are asymmetric across head sweeps. Attractive odor removal during head bends triggers rapid head withdrawal in the opposite direction. Unlike sensory encoding, this directional response is dependent on motor inputs to and synaptic output from RIA. Together, these results suggest that RIA is part of a sensorimotor pathway that is dynamically regulated according to head orientation at two levels: the first is a gate that filters sensory representations in RIA, and the second is a switch that routes RIA synaptic output to dorsal or ventral head motor neurons.

neuroscience↗

bioRxiv2017

Female grant applicants are equally successful when peer reviewers assess the science, but not when they assess the scientist

BackgroundPrevious research shows that men often receive more research funding than women, but does not provide empirical evidence as to why this occurs. In 2014, the Canadian Institutes of Health Research (CIHR) created a natural experiment by dividing all investigator-initiated funding into two new grant programs: one with and one without an explicit review focus on the caliber of the principal investigator.\n\nMethodsWe analyzed application success among 23,918 grant applications from 7,093 unique principal investigators in a 5-year natural experiment across all investigator-initiated CIHR grant programs in 2011-2016. We used Generalized Estimating Equations to account for multiple applications by the same applicant and an interaction term between each principal investigators self-reported sex and grant programs to compare success rates between male and female applicants under different review criteria.\n\nResultsThe overall grant success rate across all competitions was 15.8%. After adjusting for age and research domain, the predicted probability of funding success in traditional programs was 0.9 percentage points higher for male than for female principal investigators (OR 0.934, 95% CI 0.854-1.022). In the new program focused on the proposed science, the gap was 0.9 percentage points in favour of male principal investigators (OR 0.998, 95% CI 0.794-1.229). In the new program with an explicit review focus on the caliber of the principal investigator, the gap was 4.0 percentage points in favour of male principal investigators (OR 0.705, 95% CI 0.519- 0.960).\n\nInterpretationThis study suggests gender gaps in grant funding are attributable to less favourable assessments of women as principal investigators, not differences in assessments of the quality of science led by women. We propose ways for funders to avoid allowing gender bias to influence research funding.\n\nFundingThis study was unfunded.

scientific communication and education↗