Winnett, A. V. | bioRxiv Science

bioRxiv2025

Faecalibacterium prausnitzii, depleted in the Parkinson's disease microbiome, improves motor deficits in α-synuclein overexpressing mice

Gut microbiome composition is altered in Parkinsons disease (PD), a neurodegenerative disorder characterized by motor dysfunction and frequently accompanied by gastrointestinal (GI) symptoms. Notably, microbial taxa with anti-inflammatory properties are consistently depleted in PD patients compared to controls. To explore whether specific gut bacteria may be disease-protective, we assembled a microbial consortium of 8 human-associated taxa that are reduced in individuals with PD across multiple cohorts and geographies. Treatment of -synuclein overexpressing (Thy1-ASO) mice, an animal model of PD, with this consortium improved motor and GI deficits. A single bacterial species from this consortium, Faecalibacterium prausnitzii, was sufficient to correct gut microbiome deviations in Thy1-ASO mice, induce anti-inflammatory immune responses, and promote protective colonic gene expression profiles. Accordingly, oral treatment with F. prausnitzii robustly ameliorated motor and GI symptoms and reduced -synuclein aggregates in the brain. These findings support the emerging hypothesis of functional contributions by the microbiome to PD and embolden development of potential probiotic therapies.

physiology↗

bioRxiv2023

Efficient and accurate detection of viral sequences at single-cell resolution reveals novel viruses perturbing host gene expression

There are an estimated 300,000 mammalian viruses from which infectious diseases in humans may arise. They inhabit human tissues such as the lungs, blood, and brain and often remain undetected. Efficient and accurate detection of viral infection is vital to understanding its impact on human health and to make accurate predictions to limit adverse effects, such as future epidemics. The increasing use of high-throughput sequencing methods in research, agriculture, and healthcare provides an opportunity for the cost-effective surveillance of viral diversity and investigation of virus-disease correlation. However, existing methods for identifying viruses in sequencing data rely on and are limited to reference genomes or cannot retain single-cell resolution through cell barcode tracking. We introduce a method that accurately and rapidly detects viral sequences in bulk and single-cell transcriptomics data based on highly conserved amino acid domains, which enables the detection of RNA viruses covering over 100,000 virus species. The analysis of viral presence and host gene expression in parallel at single-cell resolution allows for the characterization of host viromes and the identification of viral tropism and host responses. We applied our method to identify putative novel viruses in rhesus macaque PBMC data that display cell type specificity and whose presence correlates with altered host gene expression.

bioinformatics↗