PTEN mutations impair CSF dynamics and cortical networks by dysregulating periventricular neural progenitors
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Genetically encoded biosensor for fluorescence lifetime imaging of PTEN dynamics in the intact brain
The phosphatase and tensin homolog (PTEN) is a vital protein that maintains an inhibitory brake for cellular proliferation and growth. Accordingly, PTEN loss-of-function mutations are associated with a broad spectrum of human pathologies. Despite its importance, there is currently no method to directly monitor PTEN activity with cellular specificity within intact biological systems. Here we describe the development of a FRET-based biosensor using PTEN conformation as a proxy for the PTEN activity state, for two-photon fluorescence lifetime imaging microscopy. We identify a point mutation that allows the monitoring of PTEN activity with minimal interference to endogenous PTEN signaling. We demonstrate imaging of PTEN activity in cell lines, intact Caenorhabditis elegans and in the mouse brain. Finally, we develop a red-shifted sensor variant that allows us to identify cell-type-specific PTEN activity in excitatory and inhibitory cortical cells. In summary, our approach enables dynamic imaging of PTEN activity in vivo with unprecedented spatial and temporal resolution.
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Soluble cerebral Aβ protofibrils link Aβ plaque pathology to changes in CSF Aβ42/Aβ40 ratios, neurofilament light and tau in Alzheimer’s disease model mice
The Aβ42/Aβ40 ratio in the cerebrospinal fluid (CSF) and the concentrations of neurofilament light (NfL) and total tau (t-tau) are changed in the early stages of Alzheimer’s disease (AD)1, but their neurobiological correlates are not entirely understood. Here, we used 5xFAD transgenic mice to investigate the associations between these CSF biomarkers and measures of cerebral Aβ, including Aβ42/Aβ40 ratios in plaques, insoluble fibrillar deposits and soluble protofibrils. A high Aβ42/Aβ40 ratio in soluble protofibrils was the strongest independent predictor of low CSF Aβ42/Aβ40 ratios and high CSF NfL and t-tau concentrations when compared to Aβ42/Aβ40 ratios in plaques and insoluble fibrillar deposits. Furthermore, the Aβ42/Aβ40 ratio in soluble protofibrils fully mediated the associations between the corresponding ratio in plaques and all the investigated CSF biomarkers. In AppNL-G-F/NL-G-F knock-in mice, protofibrils fully mediated the association between plaques and the CSF Aβ42/Aβ40 ratio. Together, the results suggest that the Aβ42/Aβ40 ratio in CSF might better reflect brain levels of soluble Aβ protofibrils than insoluble Aβ fibrils in plaques in AD. Furthermore, elevated concentrations of NfL and t-tau in CSF might be triggered by increased brain levels of soluble Aβ protofibrils.
Innovating beyond electrophysiology through multimodal neural interfaces
Neural circuits distributed across different brain regions mediate how neural information is processed and integrated, resulting in complex cognitive capabilities and behaviour. To understand dynamics and interactions of neural circuits, it is crucial to capture the complete spectrum of neural activity, ranging from the fast action potentials of individual neurons to the population dynamics driven by slow brain-wide oscillations. In this Review, we discuss how advances in electrical and optical recording technologies, coupled with the emergence of machine learning methodologies, present a unique opportunity to unravel the complex dynamics of the brain. Although great progress has been made in both electrical and optical neural recording technologies, these alone fail to provide a comprehensive picture of the neuronal activity with high spatiotemporal resolution. To address this challenge, multimodal experiments integrating the complementary advantages of different techniques hold great promise. However, they are still hindered by the absence of multimodal data analysis methods capable of providing unified and interpretable explanations of the complex neural dynamics distinctly encoded in these modalities. Combining multimodal studies with advanced data analysis methods will offer novel perspectives to address unresolved questions in basic neuroscience and to develop treatments for various neurological disorders.
The radiogenomic and spatiogenomic landscapes of glioblastoma and their relationship to oncogenic drivers
Glioblastoma is a highly heterogeneous brain tumor, posing challenges for precision therapies and patient stratification in clinical trials. Understanding how genetic mutations influence tumor imaging may improve patient management and treatment outcomes. This study investigates the relationship between imaging features, spatial patterns of tumor location, and genetic alterations in IDH-wildtype glioblastoma, as well as the likely sequence of mutational events.
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