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Register a new userMeasuring the repertoire of age-related behavioral changes in Drosophila melanogaster
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Aging affects almost all aspects of an organism -- its morphology, its physiology, its behavior. Isolating which biological mechanisms are regulating these changes, however, has proven difficult, potentially due to our inability to characterize the full repertoire of an animals behavior across the lifespan. Using data from fruit flies (D. melanogaster) we measure the full repertoire of behaviors as a function of age. We observe a sexually dimorphic pattern of changes in the behavioral repertoire during aging. Although the stereotypy of the behaviors and the complexity of the repertoire overall remains relatively unchanged, we find evidence that the observed alterations in behavior can be explained by changing the flys overall energy budget, suggesting potential connections between metabolism, aging, and behavior.
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The Drosophila melanogaster white-eyed w1118 line serves as a blank control, allowing genetic recombination of any gene of interest along with a readily recognizable marker. w1118 flies display behavioral susceptibility to environmental stimulation such as light. It is of great importance to characterize the behavioral performance of w1118 flies because this would provide a baseline from which the effect of the gene of interest could be differentiated. Little work has been performed to characterize the walking behavior in adult w1118 flies. Here we show that pulsed light stimulation increased the regularity of walking trajectories of w1118 flies in circular arenas. We statistically modeled the distribution of distances to center and extracted the walking structures of w1118 flies. Pulsed light stimulation redistributed the time proportions for individual walking structures. Specifically, pulsed light stimulation reduced the episodes of crossing over the central region of the arena. An addition of four genomic copies of mini-white, a common marker gene for eye color, mimicked the effect of pulsed light stimulation in reducing crossing in a circular arena. The reducing effect of mini-white was copy-number-dependent. These findings highlight the rhythmic light stimulation-evoked modifications of walking behavior in w1118 flies and an unexpected behavioral consequence of mini-white in transgenic flies carrying w1118 isogenic background.
Tracking the dynamics of fluorescent nanoparticles during embryonic development allows insights into the physical state of the embryo and, potentially, molecular processes governing developmental mechanisms. In this work, we investigate the motion of individual fluorescent nanodiamonds micro-injected into Drosophila melanogaster embryos prior to cellularisation. Fluorescence correlation spectroscopy and wide-field imaging techniques are applied to individual fluorescent nanodiamonds in blastoderm cells during stage 5 of development to a depth of ~40 mu m. The majority of nanodiamonds in the blastoderm cells during cellularisation exhibit free diffusion with an average diffusion coefficient of (6 $pm$ 3) x 10$^{-3}$ mu m$^2$/s, (mean $pm$ SD). Driven motion in the blastoderm cells was also observed with an average velocity of 0.13 $pm$ 0.10 mu m/s (mean $pm$ SD) mu m/s and an average applied force of 0.07 $pm$ 0.05 pN (mean $pm$ SD). Nanodiamonds in the periplasm between the nuclei and yolk were also found to undergo free diffusion with a significantly larger diffusion coefficient of (63 $pm$ 35) x10$^{-3}$ mu m$^2$/s (mean $pm$ SD). Driven motion in this region exhibited similar average velocities and applied forces compared to the blastoderm cells indicating the transport dynamics in the two cytoplasmic regions are analogous.
Fueled by breakthrough technology developments, the biological, biomedical, and behavioral sciences are now collecting more data than ever before. There is a critical need for time- and cost-efficient strategies to analyze and interpret these data to advance human health. The recent rise of machine learning as a powerful technique to integrate multimodality, multifidelity data, and reveal correlations between intertwined phenomena presents a special opportunity in this regard. However, classical machine learning techniques often ignore the fundamental laws of physics and result in ill-posed problems or non-physical solutions. Multiscale modeling is a successful strategy to integrate multiscale, multiphysics data and uncover mechanisms that explain the emergence of function. However, multiscale modeling alone often fails to efficiently combine large data sets from different sources and different levels of resolution. We show how machine learning and multiscale modeling can complement each other to create robust predictive models that integrate the underlying physics to manage ill-posed problems and explore massive design spaces. We critically review the current literature, highlight applications and opportunities, address open questions, and discuss potential challenges and limitations in four overarching topical areas: ordinary differential equations, partial differential equations, data-driven approaches, and theory-driven approaches. Towards these goals, we leverage expertise in applied mathematics, computer science, computational biology, biophysics, biomechanics, engineering mechanics, experimentation, and medicine. Our multidisciplinary perspective suggests that integrating machine learning and multiscale modeling can provide new insights into disease mechanisms, help identify new targets and treatment strategies, and inform decision making for the benefit of human health.
Drosophila melanogaster hemocytes are highly motile cells that are crucial for successful embryogenesis and have important roles in the organisms immunological response. Hemocyte motion was measured using selective plane illumination microscopy. Every hemocyte cell in one half of an embryo was tracked during embryogenesis and analysed using a deep learning neural network. The anomalous transport of the cells was well described by fractional Brownian motion that was heterogeneous in both time and space. Hemocyte motion became less persistent over time. LanB1 and SCAR mutants disrupted the collective cellular motion and reduced its persistence due to the modification of viscoelasticity and actin-based motility respectively. The anomalous motility of the hemocytes oscillated in time with alternating epoques of varying persistent motion. Touching hemocytes experience synchronised contact inhibition of locomotion; an anomalous tango. A quantitative statistical framework is presented for hemocyte motility which provides new biological insights.
Reduced motor control is one of the most frequent features associated with aging and disease. Nonlinear and fractal analyses have proved to be useful in investigating human physiological alterations with age and disease. Similar findings have not been established for any of the model organisms typically studied by biologists, though. If the physiology of a simpler model organism displays the same characteristics, this fact would open a new research window on the control mechanisms that organisms use to regulate physiological processes during aging and stress. Here, we use a recently introduced animal tracking technology to simultaneously follow tens of Caenorhabdits elegans for several hours and use tools from fractal physiology to quantitatively evaluate the effects of aging and temperature stress on nematode motility. Similarly to human physiological signals, scaling analysis reveals long-range correlations in numerous motility variables, fractal properties in behavioral shifts, and fluctuation dynamics over a wide range of timescales. These properties change as a result of a superposition of age and stress-related adaptive mechanisms that regulate motility.
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