Biology subjects

McKenna, M.

Publications and source records attributed to McKenna, M..

3 recordsLinked to original sources

bioRxiv2025

Big Data, Sound Science, Lasting Impact: a framework for passive acoustic monitoring

Marine passive acoustic monitoring (PAM) has produced petabytes of data that are used by researchers, resource managers, industry, and regulators to understand how marine animals use sound and the impacts of anthropogenic noise on species and ecosystems throughout the global ocean. These big data provide unprecedented opportunities to study underwater soundscapes and marine ecology but also enormous challenges to efficiently extract information. To address these challenges, a U.S. federally funded and led Sound Cooperative (SoundCoop) project built community-focused cyberinfrastructure to promote improved, scalable and sustainable processing and access of marine PAM data for management, science, industry and military applications. Driven by cross-institutional participation representing a diversity of data collection methods and conditions, the SoundCoop project established guidance for standardized processing of ocean sound level metrics using freeware software toolkits and developed core tools and processes that support open science. Four examples of comparative analyses that connect disparate PAM monitoring efforts, and integrate non-acoustic data illustrate how comparable, interoperable sound level metrics support a more coherent and synoptic perspective on global ocean soundscapes using methods that current and future PAM projects can leverage. Such a framework around PAM big data offers the opportunity to revolutionize large-scale marine ecology and oceanography in similar ways to other transformative approaches for understanding environmental or ecological patterns and processes at global scales.

ecology↗

bioRxiv2024

Adaptive protein synthesis in genetic models of copper deficiency and childhood neurodegeneration

Rare inherited diseases caused by mutations in the copper transporters SLC31A1 (CTR1) or ATP7A induce copper deficiency in the brain, causing seizures and neurodegeneration in infancy through poorly understood mechanisms. Here, we used multiple model systems to characterize the molecular mechanisms by which neuronal cells respond to copper deficiency. Targeted deletion of CTR1 in neuroblastoma cells produced copper deficiency that was associated with a metabolic shift favoring glycolysis over oxidative phosphorylation. Proteomic and transcriptomic analysis of CTR1 KO cells revealed simultaneous upregulation of mTORC1 and S6K signaling and reduced PERK signaling. Patterns of gene and protein expression and pharmacogenomics show increased activation of the mTORC1-S6K pathway as a pro-survival mechanism, ultimately resulting in increased protein synthesis. Spatial transcriptomic profiling of Atp7aflx/Y :: Vil1Cre/+ mice identified upregulated protein synthesis machinery and mTORC1-S6K pathway genes in copper-deficient Purkinje neurons in the cerebellum. Genetic epistasis experiments in Drosophila demonstrated that copper deficiency dendritic phenotypes in class IV neurons are partially rescued by increased S6k expression or 4E-BP1 (Thor) RNAi, while epidermis phenotypes are exacerbated by Akt, S6k, or raptor RNAi. Overall, we demonstrate that increased mTORC1-S6K pathway activation and protein synthesis is an adaptive mechanism by which neuronal cells respond to copper deficiency. SignificanceO_LICopper deficiency is present in rare conditions such as Menkes disease and CTR1 deficiency and in more common diseases like Alzheimers. The mechanisms of resilience and ultimate susceptibility to copper deficiency and associated pathology in the brain remain unknown. C_LIO_LIWe demonstrate that in a human cell line, Drosophila, and the mouse cerebellum, copper-deficient neuronal cells exhibit increased protein synthesis through mTORC1 activation and decreased PERK (EIF2AK3) activity. C_LIO_LIUpregulation of protein synthesis facilitates resilience of neuronal cells to copper deficiency, including partial restoration of dendritic arborization. Our findings offer a new framework for understanding copper deficiency-related pathology in neurological disorders. C_LI

neuroscience↗

bioRxiv2020

Multiple particle tracking detects changes in brain extracellular matrix structure and predicts neurodevelopmental age

Abstract SummaryBrain extracellular matrix (ECM) structure mediates many aspects of neuronal function. Probing changes in ECM structure could provide insights into aging and neurological disease. Herein, we demonstrate the ability to characterize changes in brain ECM structure using multiple particle tracking (MPT). MPT was carried out in organotypic rat brain slices to detect induced and naturally occurring changes in ECM structure. Induced degradation of neural ECM led to a significant increase in nanoparticle diffusive ability in the brain extracellular space. For structural changes that occur naturally during development, an inverse relationship existed between age and nanoparticle diffusion. Using the age-dependent dataset, we applied extreme gradient boosting (XGBoost) to generate models capable of classifying nanoparticle trajectories. Collectively, this work demonstrates the utility of MPT combined with machine learning for measuring changes in brain ECM structure and predicting associated complex features such as developmental age.

developmental biology↗