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Vincent, T.

Publications and source records attributed to Vincent, T..

2 recordsLinked to original sources

Molecular features of RNA silencing against phloem-restricted polerovirus TuYV enable amplification of silencing signal from host transcripts

In plants and some animal lineages, RNA silencing is an efficient and adaptable defense mechanism against viruses. To counter it, viruses encode suppressor proteins that interfere with RNA silencing. Phloem-restricted viruses are spreading at an alarming rate and cause substantial reduction of crop yield, but how they interact with their hosts at the molecular level is still insufficiently understood. Here, we investigate the antiviral response against phloem-restricted turnip yellows virus (TuYV) in the model plant Arabidopsis thaliana. Using a combination of genetics, deep sequencing, and mechanical vasculature enrichment, we show that the main axis of silencing active against TuYV involves 22-nt vsiRNA production by DCL2, and their preferential loading into AGO1. Unexpectedly, and despite the viral encoded VSR P0 previously shown to mediate degradation of AGO proteins, vascular AGO1 undergoes specific post-translational stabilization during TuYV infection. We also identify vascular novel secondary siRNA produced from conserved plant transcripts and initiated by DCL2-processed AGO1-loaded vsiRNA, supporting a viral strategy to modulate host response. Collectively, our work uncovers the complexity of antiviral RNA silencing against phloem-restricted TuYV and prompts a re-assessment of the role of its suppressor of silencing P0 during genuine infection.

plant biology

Diffuse optical reconstructions of NIRS data using Maximum Entropy on the Mean

Functional near-infrared spectroscopy (fNIRS) measures the hemoglobin concentration changes associated with neuronal activity. Diffuse optical tomography (DOT) consists of reconstructing the optical density changes measured from scalp channels to the oxy-/deoxy-hemoglobin (i.e., HbO/HbR) concentration changes within the cortical regions. In the present study, we adapted a nonlinear source localization method developed and validated in the context of Electro- and Magneto-Encephalography (EEG/MEG): the Maximum Entropy on the Mean (MEM), to solve the inverse problem of DOT reconstruction. We first introduced depth weighting strategy within the MEM framework for DOT reconstruction to avoid biasing the reconstruction results of DOT towards superficial regions. We also proposed a new initialization of the MEM model improving the temporal accuracy of the original MEM framework. To evaluate MEM performance and compare with widely used depth weighted Minimum Norm Estimate (MNE) inverse solution, we applied a realistic simulation scheme which contained 4000 simulations generated by 250 different seeds at different locations and 4 spatial extents ranging from 3 to 40cm2 along the cortical surface. Our results showed that overall MEM provided more accurate DOT reconstructions than MNE. Moreover, we found that MEM was remained particularly robust in low signal-to-noise ratio (SNR) conditions. The proposed method was further illustrated by comparing to functional Magnetic Resonance Imaging (fMRI) activation maps, on real data involving finger tapping tasks with two different montages. The results showed that MEM provided more accurate HbO and HbR reconstructions in spatial agreement with the main fMRI cluster, when compared to MNE. HighlightsO_LIWe introduced a new fNIRS reconstruction method - Maximum Entropy on the Mean. C_LIO_LIWe implemented depth weighting strategy within the MEM framework. C_LIO_LIWe improved the temporal accuracy of the original MEM reconstruction. C_LIO_LIPerformances of MEM and MNE were evaluated with realistic simulations and real data. C_LIO_LIMEM provided more accurate and robust reconstructions than MNE. C_LI

neuroscience