Biology subjects

Volpe, G.

Publications and source records attributed to Volpe, G..

22 records · Page 2Linked to original sources

bioRxiv2020

Single-cell regulatory landscape and disease vulnerability map of adult Macaque cortex

Single cell approaches have increased our knowledge about the cell type composition of the non-human primate (NHP), but a detailed characterization of area-specific regulatory features remains outstanding. We generated single-cell chromatin accessibility (single-cell ATAC) and transcriptomic data of 358,237 cells from prefrontal cortex (PFC), primary motor cortex (M1) and primary visual cortex (V1) of adult cynomolgus monkey brain, and integrated this dataset with Stereo-seq (Spatio-Temporal Enhanced REsolution Omics-sequencing) of the corresponding cortical areas to assign topographic information to molecular states. We identified area-specific chromatin accessible sites and their targeted genes, including the cell type-specific transcriptional regulatory network associated with excitatory neurons heterogeneity. We reveal calcium ion transport and axon guidance genes related to specialized functions of PFC and M1, identified the similarities and differences between adult macaque and human oligodendrocyte trajectories, and mapped the genetic variants and gene perturbations of human diseases to NHP cortical cells. This resource establishes a transcriptomic and chromatin accessibility combinatory regulatory landscape at a single-cell and spatially resolved resolution in NHP cortex.

neuroscience↗

bioRxiv2020

Single-cell atlas of a non-human primate reveals new pathogenic mechanisms of COVID-19

Stopping COVID-19 is a priority worldwide. Understanding which cell types are targeted by SARS-CoV-2 virus, whether interspecies differences exist, and how variations in cell state influence viral entry is fundamental for accelerating therapeutic and preventative approaches. In this endeavor, we profiled the transcriptome of nine tissues from a Macaca fascicularis monkey at single-cell resolution. The distribution of SARS-CoV-2 facilitators, ACE2 and TMRPSS2, in different cell subtypes showed substantial heterogeneity across lung, kidney, and liver. Through co-expression analysis, we identified immunomodulatory proteins such as IDO2 and ANPEP as potential SARS-CoV-2 targets responsible for immune cell exhaustion. Furthermore, single-cell chromatin accessibility analysis of the kidney unveiled a plausible link between IL6-mediated innate immune responses aiming to protect tissue and enhanced ACE2 expression that could promote viral entry. Our work constitutes a unique resource for understanding the physiology and pathophysiology of two phylogenetically close species, which might guide in the development of therapeutic approaches in humans. Bullet pointsO_LIWe generated a single-cell transcriptome atlas of 9 monkey tissues to study COVID-19. C_LIO_LIACE2+TMPRSS2+ epithelial cells of lung, kidney and liver are targets for SARS-CoV-2. C_LIO_LIACE2 correlation analysis shows IDO2 and ANPEP as potential therapeutic opportunities. C_LIO_LIWe unveil a link between IL6, STAT transcription factors and boosted SARS-CoV-2 entry. C_LI

cell biology↗

bioRxiv2019

A portable and cost-effective microfluidic system for massively parallel single-cell transcriptome profiling

Single-cell technologies are becoming increasingly widespread and have been revolutionizing our understanding of cell identity, state, diversity and function. However, current platforms can be slow to apply to large-scale studies and resource-limited clinical arenas due to a variety of reasons including cost, infrastructure, sample quality and requirements. Here we report DNBelab C4 (C4), a negative pressure orchestrated, portable and cost-effective device that enables high-throughput single-cell transcriptional profiling. C4 system can efficiently allow discrimination of species-specific cells at high resolution and dissect tissue heterogeneity in different organs, such as murine lung and cerebral cortex. Finally, we show that the C4 system is comparable to existing platforms but has huge benefits in cost and portability and, as such, it will be of great interest for the wider scientific community.

genomics↗

bioRxiv2017

BRAPH: A Graph Theory Software for the Analysis of Brain Connectivity

The brain is a large-scale complex network whose workings rely on the interaction between its various regions. In the past few years, the organization of the human brain network has been studied extensively using concepts from graph theory, where the brain is represented as a set of nodes connected by edges. This representation of the brain as a connectome can be used to assess important measures that reflect its topological architecture. We have developed a freeware MatLab-based software (BRAPH - BRain Analysis using graPH theory) for connectivity analysis of brain networks derived from structural magnetic resonance imaging (MRI), functional MRI (fMRI), positron emission tomography (PET) and electroencephalogram (EEG) data. BRAPH allows building connectivity matrices, calculating global and local network measures, performing non-parametric permutations for group comparisons, assessing the modules in the network, and comparing the results to random networks. By contrast to other toolboxes, it allows performing longitudinal comparisons of the same patients across different points in time. Furthermore, even though a user-friendly interface is provided, the architecture of the program is modular (object-oriented) so that it can be easily expanded and customized. To demonstrate the abilities of BRAPH, we performed structural and functional graph theory analyses in two separate studies. In the first study, using MRI data, we assessed the differences in global and nodal network topology in healthy controls, patients with amnestic mild cognitive impairment, and patients with Alzheimers disease. In the second study, using resting-state fMRI data, we compared healthy controls and Parkinsons patients with mild cognitive impairment.

neuroscience↗