Biology subjects

Thrupp, N.

Publications and source records attributed to Thrupp, N..

7 recordsLinked to original sources

bioRxiv2026

Multimodal profiling and intersectional genetics reveal CA1 border inhibitory neuron diversity and postnatal emergence of retrosplenial connectivity

Inhibitory neurons (INs) at the stratum radiatum/stratum lacunosum-moleculare border of hippocampal CA1 comprise diverse populations, including long-range-projecting neurons that innervate the retrosplenial cortex (RSCtx). However, their molecular organization and developmental connectivity remain poorly understood. Here, we combine multimodal transcriptomic profiling, intersectional genetics, and retrograde tracing to characterize CA1 border INs. We identified two major caudal ganglionic eminence-derived, Cxcl14-enriched populations distinguished by Syt6/Cck-related and Ntng1-expressing transcriptional profiles. We then generated a Cxcl14-Cre mouse line that, when combined with an IN-specific viral enhancer, provides genetic access to CA1 border INs. Retrograde labeling established that CA1 INs projecting to the RSCtx belong to the Ntng1-expressing population, and that this long-range projection emerges during postnatal mouse development, between postnatal days 3 and 5. Finally, analysis of genes encoding cell-surface proteins, key regulators of connectivity, revealed distinct expression profiles in RSCtx-projecting and SYT6-positive INs. Together, these findings establish a molecular and developmental framework for CA1 border IN diversity and provide a genetic strategy for investigating the assembly and function of these inhibitory circuits.

neuroscience↗

bioRxiv2026

An Open Benchmark for Systems Vaccinology: Insights from the CMI-PB Challenges

Systems vaccinology approaches have identified factors affecting vaccine responses in multiple studies, but the ability of computational models to generalize these findings to unseen data remains unclear. We established a community resource to create and compare models predicting B. pertussis booster vaccination responses and put such modeling approaches to the test. We compiled multi-modal experimental training data from three independent cohorts (n=117 individuals), and asked investigators to predict vaccine responses in a cohort of 54 newly recruited individuals using only their pre-booster vaccination data. We benchmarked a total of 107 computational models. Top-performing models were characterized by workflows that prioritized rigorous data preprocessing, robust imputation of missing data, and the use of multi-omics integration or non-linear machine learning. We identified pre-existing antigen-specific antibody titers and baseline monocyte frequencies as the most consistent predictors of post-vaccination immunity, highlighting the dominant role of individual immune setpoints. We established the resulting datasets and evaluation framework as a community resource to advance predictive immunology and facilitate personalized vaccination strategies.

immunology↗

bioRxiv2024

Putting computational models of immunity to the test - an invited challenge to predict B. pertussis vaccination outcomes

Systems vaccinology studies have been used to build computational models that predict individual vaccine responses and identify the factors contributing to differences in outcome. Comparing such models is challenging due to variability in study designs. To address this, we established a community resource to compare models predicting B. pertussis booster responses and generate experimental data for the explicit purpose of model evaluation. We here describe our second computational prediction challenge using this resource, where we benchmarked 49 algorithms from 53 scientists. We found that the most successful models stood out in their handling of nonlinearities, reducing large feature sets to representative subsets, and advanced data preprocessing. In contrast, we found that models adopted from literature that were developed to predict vaccine antibody responses in other settings performed poorly, reinforcing the need for purpose-built models. Overall, this demonstrates the value of purpose-generated datasets for rigorous and open model evaluations to identify features that improve the reliability and applicability of computational models in vaccine response prediction.

immunology↗

bioRxiv2022

Long noncoding RNA MEG3 activates neuronal necroptosis in Alzheimer's disease

Abstract/SummaryNeuronal cell loss is a defining feature of Alzheimers disease (AD), but it remains unclear how neurons die and how this relates to other defining characteristics of the disease1. Existing in vivo AD models only partially recapitulate the neuropathology of AD with very mild or no neuronal cell loss. Here we demonstrate that human neurons xenografted in mouse brain exposed to amyloid pathology develop sarkosyl-insoluble tau filaments, positive Gallyas silver staining, release phosphorylated tau (P-tau181) into the blood, and display considerable neuronal cell loss, providing a model for the induction of full Tau pathology by simple exposure to amyloid pathology in AD. The alterations are specific to human neurons and contrast with the mild effects exhibited in mouse neurons. A core transcriptional program in the human neurons is characterized by strong upregulation of MEG3, a neuron-specific long noncoding RNA. MEG3 is also strongly upregulated in neurons from AD patients in situ. MEG3 expression alone is sufficient to induce necroptosis in human neurons in vitro. Orally administered small molecule receptor-interacting protein (RIP) kinase -1 and -3 inhibitors rescued the neuronal cell loss in this novel AD model. Thus, xenografted human neurons are uniquely sensitive to amyloid pathology, recapitulate all the defining neuropathological features of AD, and ultimately die by necroptosis.

neuroscience↗

bioRxiv2021

Melanin Concentrating Hormone- and sleep-dependent synaptic downscaling is impaired in Alzheimer's Disease

In Alzheimers disease (AD), pathophysiological changes in the hippocampus cause deficits in episodic memory formation, leading to cognitive impairment 1,2. Neuronal hyperactivity is observed early in AD 3,4. Here, we find that homeostatic mechanisms transiently counteract increased neuronal activity in the hippocampal CA1 region of the AppNL-G-F humanized knock-in mouse model for AD 5, but ultimately fail to maintain neuronal activity at set-point. Spatial transcriptomic analysis in CA1 during the homeostatic response identifies the Melanin-Concentrating Hormone (MCH)-encoding gene. MCH is expressed in sleep-active lateral hypothalamic neurons that project to CA1 and modulate memory 6. We show that MCH regulates synaptic plasticity genes and synaptic downscaling in hippocampal neurons. Furthermore, MCH-neuron activity is impaired in AppNL-G-F mice, disrupting sleep-dependent homeostatic plasticity and stability of neuronal activity in CA1. Finally, we find perturbed MCH-axon morphology in CA1 early in AppNL-G-F mice and in AD patients. Our work identifies dysregulation of the MCH-system as a key player in aberrant neuronal activity in the early stages of AD.

neuroscience↗

bioRxiv2020

Single nucleus sequencing fails to detect microglial activation

Single nucleus RNA-Seq (snRNA-Seq) methods are used as an alternative to single cell RNA-Seq methods, as they allow transcriptomic profiling of frozen tissue. However, it is unclear whether snRNA-Seq is able to detect cellular state in human tissue. Indeed, snRNA-Seq analyses of human brain samples have failed to detect a consistent microglial activation signature in Alzheimers Disease. A comparison of microglia from single cells and single nuclei of four human subjects reveals that ~1% of genes is depleted in nuclei compared to whole cells. This small population contains 18% of genes previously implicated in microglial activation, including APOE, CST3, FTL, SPP1, and CD74. We confirm our findings across multiple previous single nucleus and single cell studies. Given the low sensitivity of snRNA-Seq to this population of activation genes, we conclude that snRNA-Seq is not suited to detecting cellular activation in microglia in human disease.

neuroscience↗

bioRxiv2020

Impaired adult hippocampal neurogenesis in Alzheimer's disease is mediated by microRNA-132 deficiency and can be restored by microRNA-132 replacement

SummaryAdult hippocampal neurogenesis (AHN) plays a crucial role in memory processes and is impeded in the brains of Alzheimers disease (AD) patients. However, the molecular mechanisms impacting AHN in AD brain are unknown. Here we identify miR-132, one of the most consistently downregulated microRNAs in AD, as a novel mediator of the AHN deficits in AD. The effects of miR-132 are cell-autonomous and its overexpression is proneurogenic in the adult neurogenic niche in vivo and in human neural stem cells in vitro. miR-132 knockdown in wild-type mice mimics neurogenic deficits in AD mouse brain. Restoring miR-132 levels in mouse models of AD significantly restores AHN and relevant memory deficits. Our findings provide mechanistic insight into the hitherto elusive functional significance of AHN in AD and designate miR-132 replacement as a novel therapeutic strategy to rejuvenate the AD brain and thereby alleviate aspects of memory decline.

neuroscience↗