bioRxiv Science⌕ Search

bioRxiv · 10.1101/2024.04.29.591341

Fungi activate Toll-1 dependent immune evasion to induce cell loss in the host brain

Abstract

Fungi evolve within the host, ensuring their own nutrition and reproduction, at the expense of host health. They intervene in hosts brain function, to alter host behaviour and induce neurodegeneration. In humans, fungal infections are emerging as drivers of neuroinflammation, neurodegenerative diseases and psychiatric disorders. However, how fungi alter the host brain is unknown. Fungi trigger an innate immune response mediated by the Toll-1/TLR receptor, the adaptor MyD88 and the transcription factor Dif/NF{kappa}B, that induce the expression of antimicrobial peptides (AMPs). However, in the nervous system, Toll-1/TLR could also drive an alternative pathway involving the adaptor Sarm, which causes cell death instead. Sarm is the universal inhibitor of MyD88 and could drive immune evasion. The entomopathogenic fungus Beauveria bassiana is well-known to activate Toll-1 signalling in innate immunity in Drosophila. In fruit-flies, the adaptor Wek links Toll-1 to Sarm. Thus, here we asked whether B. bassiana could damage the Drosophila brain via Toll-1, Wek and Sarm. We show that exposure to B. bassiana reduced fly lifespan and impaired locomotion. B. bassiana entered the brain and induced the up-regulation of AMPs, as well as wek and sarm, within the brain. Exposure to B. bassiana caused neuronal and glial loss in the adult Drosophila brain. Importantly, RNAi knockdown of Toll-1, wek or sarm concomitantly with infection prevented B. bassiana induced cell loss. By contrast, over-expression of wek or sarm was sufficient to cause dopaminergic neuron loss in the absence of infection. These data show that B. bassiana caused cell loss in the host brain via Toll-1/Wek/Sarm signalling driving immune evasion. We conclude that pathogens can benefit from an innate immunity receptor to damage the host brain. A similar activation of Sarm downstream of TLRs in response to fungal infections could underlie psychiatric and neurodegenerative diseases in humans.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Singh, D. N. D., Roberts, A. R. E., Quesada Moraga, E., Alliband, D., Ballou, E. R., Tsai, H.-J., Hidalgo, A.. 2024-04-30. Fungi activate Toll-1 dependent immune evasion to induce cell loss in the host brain. https://doi.org/10.1101/2024.04.29.591341

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience↗

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience↗

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience↗