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Biology subjects

Carneiro, P.

Publications and source records attributed to Carneiro, P..

2 recordsLinked to original sources

A mitochondrial program encodes brain vascular reserve

Brain resilience depends on collateral vessels whose geometries preserve blood flow when primary arteries are perturbed. How these protective vascular architectures are developmentally established remains unknown. Using longitudinal in vivo imaging in zebrafish, we show that mitochondrial state in embryonic angiogenic tip cells encodes the topology of basal and surface brain collateral networks. Mechanistically, microRNA-125a establishes the bioenergetic and redox balance of endothelial tip-cell mitochondria through conserved repression of the metabolic regulator PGC1a. Disruption of the microRNA-125a-PGC1a axis uncouples mitochondrial capacity from redox buffering in developing brain tip cells, redirecting their migration toward sparse, incompletely connected collateral network topologies and increasing adult cerebrovascular vulnerability. Consistent with this mechanism, humans with subclinical cerebrovascular injury exhibit reduced circulating microRNA-125a levels associated with incomplete basal collateral configurations. Together, these findings identify mitochondrial state as an instructive and conserved developmental program that encodes brain vascular reserve.

developmental biology↗

Pynoma, PyABraOM and BIOVARS: Towards genetic variant data acquisition and integration

MotivationAdvances in genomic sequencing of human populations have generated a large amount of genomics data deposited in multiple sources. Programmatic batch searches executed at once are of great scientific interest to ease genomic investigations by retrieving and integrating this massive and decentralized data with little manual intervention. ResultsPynoma and PyABraOM APIs were developed to offer multiple queries in gnomAD and ABraOM databases, respectively. A centralized search in these databases with data integration is offered by a third API, BIOVARS, which combines the resulting information with statistical and graphical visualizations. The implemented features are demonstrated in a case study using ACE2, ADAM17 and TMPRSS2 genes, which presents a generalizable workflow that shows how our APIs facilitate the access and integration of valuable biological data. AvailabilityAll the APIs are written in Python 3. Graphical visualizations for the retrieved data are provided by using the R language version 4.1. The source codes are publicly available and hosted on GitHub (github.com/bioinfo-hcpa). Contactumatte@hcpa.edu.br Supplementary informationSupplementary data is available at github@nbioinfo-hcpa.

bioinformatics↗