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Okekenwa, S.

Publications and source records attributed to Okekenwa, S..

2 recordsLinked to original sources

Dynamic conformational ensembles of soluble Tau encode neuronal toxicity prior to aggregation

Tau aggregation is a defining feature of Alzheimers disease and related tauopathies, yet the conformational states of Tau in neurons prior to aggregation remain poorly understood. Existing structural models are derived largely from fibrillar assemblies and provide limited insight into the dynamic, soluble Tau species that initiate pathology. Here, we combine hydrogen-deuterium exchange mass spectrometry with super-resolution imaging and neuronal models to define the conformational ensemble of soluble Tau under physiological and disease-relevant conditions. We show that soluble Tau populates distinct, dynamic conformations characterized by regional stabilization and long-range intramolecular interactions that are invisible to fibril-based structures. Disease-associated perturbations selectively remodel these conformational ensembles, exposing aggregation-prone regions and altering Tau subcellular organization in neurons. Notably, these Tau species inhibit axonal transport, which is essential for neuronal health, linking specific ensemble states to neuronal toxicity. These findings establish soluble Tau conformation as a dynamic, regulatable state that precedes aggregation and encodes disease relevance. By defining the structural logic of Tau before fibril formation, this work provides a framework for understanding early tauopathy mechanisms and for targeting Tau pathology at its earliest stages. SUMMARYTau pathology is a hallmark of Alzheimers disease (AD) and related dementias (ADRDs). Although Tau is often described as intrinsically disordered, it is a dynamic protein with distinct but poorly defined conformations. Here we conduct a systematic time-resolved structure-function analysis of normal and pathologic Tau, including hyperphosphorylated, mutant Tau, and posttranslational-modification-mimetic Tau. To characterize dynamic conformational changes of Tau, we combined state-of-the-art hydrogen deuterium exchange mass spectrometry with structured illumination microscopy, demonstrating a novel Tau-MT binding mode: "dynamic oscillation". To correlate Tau structure with neuronal function, we evaluated axonal transport as a sensitive readout of neuronal health. Many toxic Tau forms share a common signature of increased exposure of the N-terminal phosphate activating domain (PAD) in vitro and in vivo. Aberrant exposure of PAD correlates with Tau pathology and axonal transport defects. Tau phosphorylation at S262 alone is sufficient to alter Tau-microtubule interactions beyond R1-R4 motifs, globally changing Tau conformation, disrupting "dynamic oscillation" on MTs, and inhibiting axonal transport. Frontotemporal dementia-associated P301L-Tau remains associated with microtubules but also inhibits axonal transport. Our results reveal a well-defined conformation of soluble WT Tau in neurons and its highly dynamic interaction with microtubules, altered by AD/ADRD-Tau forms. Our multidisciplinary approach comprising biochemical manipulations, innovative MS tools, advanced microscopy, cellular assays, and mouse and human data pair Tau conformations with distinct neuronal functions and pathologies in health and disease.

neuroscience↗

Lightweight open-source fine-tuning of SAM2 enables domain-specific microscopy segmentation

Quantitation of structures is a critical step in analyzing images. Automated segmentation of biological samples remains a central challenge in microscopy, where variations in signal/noise, intensity, texture, and edges hinder accurate delineation of cellular and tissue structures. Adaptations of foundation models such as Segment Anything Model (SAM) remain computationally intensive and require large training datasets. Here, we introduce a lightweight, open-source Google Colab pipeline that enables efficient fine-tuning of SAM2 on domain-specific datasets without additional architectural layers or specialized hardware. By coupling mask-decoder fine-tuning with biologically informed post-processing, our framework achieves robust segmentation across diverse imaging modalities. Applied to hippocampal segmentation in brain images and single-cell segmentation in cell images, fine-tuned SAM2 demonstrates substantial gains of accuracy relative to basic SAM2 and matches leading tools. This work establishes a scalable and accessible paradigm for domain-specific adaptations of SAM2 in microscopy, lowering computational and data barriers to advanced image segmentation. HighlightsO_LILightweight fine-tuning with no added architectural complexity. C_LIO_LIHigh segmentation accuracy (Dice/Jaccard scores) achieved with small datasets. C_LIO_LICross-domain generalization across tissue and cell imaging with biologically informed post-processing. C_LIO_LIComparable or superior performance to widely used tools (Cellpose, Imaris, ilastik) at substantially lower computational cost. C_LIO_LIOpen-source and executable in a single Colab notebook, ensuring reproducibility and accessibility for non-computational users. C_LIO_LITurnkey adaptability, allowing researchers to transform raw microscopy data into fine-tuned SAM2 models with minimal input. C_LI

cell biology↗