Epigenome is sensitive to metabolic inputs and crucial for aging. Lysosomes emerge as a signaling hub to sense metabolic cues and regulate longevity. We unveil that lysosomal metabolic pathways signal through the epigenome to regulate transgenerational longevity in Caenorhabditis elegans. We discovered that the induction of lysosomal lipid signaling and lysosomal AMP-activated protein kinase (AMPK), or the reduction of lysosomal mechanistic-target-of-rapamycin (mTOR) signaling, increases the expression of histone H3.3 variant and elevates H3K79 methylation, leading to lifespan extension across multiple generations. This transgenerational pro-longevity effect requires intestine-to-germline transportation of H3.3 and a germline-specific H3K79 methyltransferase, and can be recapitulated by overexpressing H3.3 or the H3K79 methyltransferase. This work uncovers a lysosome-epigenome signaling axis linking soma and germline to mediate the transgenerational inheritance of longevity.Competing Interest StatementThe authors have declared no competing interest.National Institutes of Health, RF1AG074540, DP1DK113644Howard Hughes Medical Institute, https://ror.org/006w34k90

Large axon-diameter descending neurons are metabolically costly but transmit information rapidly from sensory neurons in the brain to motor neurons in the nerve cord. They have thus endured as a common feature of escape circuits in many animal species where speed is paramount. Though often considered isolated command neurons triggering fast-reaction-time, all-or-none escape responses, giant neurons are just one of multiple parallel pathways enabling selection between behavioral alternatives. Such degeneracy among escape circuits makes it unclear if and how giant neurons benefit prey fitness. Here we competed Drosophila melanogaster flies with genetically-silenced Giant Fibers (GFs) against flies with functional GFs in an arena with wild-caught damselfly predators and find that GF silencing decreases prey survival. Kinematic analysis of damselfly attack trajectories shows that decreased prey survival fitness results from GF-silenced flies failing to escape during predator attack speeds and approach distances that would normally elicit successful escapes. When challenged with a virtual looming predator, fly GFs promote survival by enforcing selection of a short-duration takeoff sequence as opposed to reducing reaction time. Our findings support a role for the GFs in promoting prey survival by influencing action selection as a means to enhance escape performance during realistically complex predation scenarios.

Preprint: https://www.biorxiv.org/content/early/2024/05/01/2024.04.30.591368

Calreticulin (CALR) is primarily an endoplasmic reticulum chaperone protein that also plays a key role in facilitating programmed cell removal (PrCR) by acting as an "eat-me" signal for macrophages, directing their recognition and engulfment of dying, diseased, or unwanted cells. Recent findings have demonstrated that macrophages can transfer their own CALR onto exposed asialoglycans on target cells, marking them for PrCR. Despite the critical role CALR plays in this process, the molecular mechanisms behind its secretion by macrophages and the formation of binding sites on target cells remain unclear. Our findings show that CALR undergoes C-terminal cleavage upon secretion, producing a truncated form that functions as the active eat-me signal detectable on target cells. We identify cathepsins as potential proteases involved in this cleavage process. Furthermore, we demonstrate that macrophages release neuraminidases, which modify the surface of target cells and facilitate CALR binding. These insights reveal a coordinated mechanism through which lipopolysaccharide (LPS)-activated macrophages regulate CALR cleavage and neuraminidase activity to mark target cells for PrCR. How they recognize the cells to be targeted remains unknown.

Super-resolution microscopy (SRM) has undeniable potential for scientific discovery, yet still presents many challenges that hinder its widespread adoption, including technical trade-offs between resolution, speed and photodamage, as well as limitations in imaging live samples and larger, more complex biological structures. Furthermore, SRM often requires specialized expertise and complex instrumentation, which can deter biologists from fully embracing the technology. In this Perspective, a follow-up to our recent Q&A article, we aim to demystify these challenges by addressing common questions and misconceptions surrounding SRM. Experts offer practical insights into how biologists can maximize the benefits of SRM while navigating issues such as photobleaching, image artifacts and the limitations of existing techniques. We also highlight recent developments in SRM that continue to push the boundaries of resolution. Our goal is to equip researchers with the crucial knowledge they need to harness the full potential of SRM.

Epigenome is sensitive to metabolic inputs and crucial for aging. Lysosomes emerge as a signaling hub to sense metabolic cues and regulate longevity. We unveil that lysosomal metabolic pathways signal through the epigenome to regulate transgenerational longevity in Caenorhabditis elegans. We discovered that the induction of lysosomal lipid signaling and lysosomal AMP-activated protein kinase (AMPK), or the reduction of lysosomal mechanistic-target-of-rapamycin (mTOR) signaling, increases the expression of histone H3.3 variant and elevates H3K79 methylation, leading to lifespan extension across multiple generations. This transgenerational pro-longevity effect requires intestine-to-germline transportation of H3.3 and a germline-specific H3K79 methyltransferase, and can be recapitulated by overexpressing H3.3 or the H3K79 methyltransferase. This work uncovers a lysosome-epigenome signaling axis linking soma and germline to mediate the transgenerational inheritance of longevity.Competing Interest StatementThe authors have declared no competing interest.National Institutes of Health, RF1AG074540, DP1DK113644Howard Hughes Medical Institute, https://ror.org/006w34k90

All brain functions in animals rely upon neuronal connectivity that is established during early development. Although the activity-dependent mechanisms are deemed important for brain development and adult synaptic plasticity, the precise cellular and molecular mechanisms remain however, largely unknown. This lack of fundamental knowledge regarding developmental neuronal assembly owes its existence to the complexity of the mammalian brain as cell-cell interactions between individual neurons cannot be investigated directly. Here, we used individually identified synaptic partners from Lymnaea stagnalis to interrogate the role of neuronal activity patterns over an extended time period during various growth time points and synaptogenesis. Using intracellular recordings, microelectrode arrays, and time-lapse imaging, we identified unique patterns of activity throughout neurite outgrowth and synapse formation. Perturbation of voltage-gated Ca channels compromised neuronal growth patterns which also invoked a protein kinase A mediated pathway. Our findings underscore the importance of unique activity patterns in regulating neuronal growth, neurite branching, and synapse formation, and identify the underlying cellular and molecular mechanisms.

Comprehensive mapping of neural connections is essential for understanding brain function. Existing automated methods for connectome reconstruction from high-resolution images of brain tissue introduce errors that require extensive and time-consuming manual correction, a critical bottleneck in the field. To address this, we developed PATHFINDER, an AI system that segments volumetric image data, identifies potential ways to assemble neuron fragments, and evaluates the plausibility of resulting shapes to reconstruct complete neurons. Using a dataset of all axons in an IBEAM-mSEM volume of mouse cortex, we show that PATHFINDER reduces the error rate in axon reconstruction by an order of magnitude over previous state of the art, leading to an improvement in proofreading throughput of up to 84× relative to prior estimates in the context of a whole mouse brain. By drastically reducing the manual effort required for analysis, this advance unlocks the potential for both large-scale connectome mapping and routine investigation of smaller volumes.

The formation of the primitive heart tube from cardiomyocytes and endocardial cells is a key event in mammalian development. Previous studies suggested that cardiomyocytes and endocardial cells segregate from a shared cardiac progenitor around the onset of gastrulation, yet their lineage relationship with other mesodermal tissues remains unclear. Using retrospective and prospective clonal analyses in mouse embryos, we traced cardiomyocyte and endocardial progenitors from the primitive streak to the heart tube. Our results identify two independent mesodermal populations specified around gastrulation onset. While each of these populations is unipotent in producing cardiomyocytes or endocardium, they retain multipotency and contribute to different subsets of non-cardiac mesoderm. Nonetheless, live imaging identifies simultaneous ingression and intermingling of these two mesodermal lineages in the primitive streak, showing their coordinated specification and migration. The proposed model for cardiac progenitor specification will help understanding the origins of congenital heart diseases and designing tissue engineering strategies.

Voltage imaging is a promising technique for high-speed recording of neuronal population activity. However, tissue scattering severely limits its application in dense neuronal populations. Here, we adopted the principle of localization microscopy, a technique that enables super-resolution imaging of single-molecules, to resolve dense neuronal activities in vivo. Leveraging the sparse activation of neurons during action potentials (APs), we precisely localize the fluorescence change associated with each AP, creating a super-resolution image of neuronal activities. This approach, termed Activity Localization Imaging (ALI), identifies overlapping neurons and separates their activities with over 10-fold greater precision than what tissue scattering permits. Using ALI, we simultaneously recorded over a hundred densely-labeled CA1 neurons, creating a map of hippocampal theta oscillation at single-cell and single-cycle resolution.

Preprint: https://doi.org/10.1101/2023.12.03.56840