Biology subjects

Cubero, R. J. A.

Publications and source records attributed to Cubero, R. J. A..

3 recordsLinked to original sources

bioRxiv2022

A systematic characterization of intrinsically formed microglia-like cells during retinal organoid differentiation.

Brain organoids differentiated from human induced pluripotent stem cells provide a unique opportunity to investigate the development, organization and connectivity of neurons in a complex cellular environment. However, organoids usually lack microglia, brain-resident immune cells which are both present in the early human embryonic brain and participate in neuronal circuit development. Here, we find that microglia innately develop in unguided retinal organoid differentiation between week 3 and 4 in 2.5D culture and appear later in floating, non-pigmented, 3D-cystic compartments. We enriched for cystic structures using a low-dosed BMP4 application and performed mass spectrometry, thus defining the protein composition of microglia-containing compartments. We found that cystic compartments expressed both mesenchymal and epithelial markers with microglia enriched in the mesenchymal region. Interestingly, microglia-like cells started to express the border-associated macrophage marker CD163. The preferential localization of human microglia to a mesenchymal compartment provides insight into the behavior and migration of microglia. The model will ultimately allow detailed study of these enigmatic cells and how they enter and distribute within the human brain.

neuroscience↗

bioRxiv2021

Microglial MorphOMICs unravel region- and sex-dependent morphological phenotypes from postnatal development to degeneration

Microglia contribute to tissue homeostasis in physiological conditions with environmental cues influencing their ever-changing morphology. Strategies to identify these changes usually involve user-selected morphometric features, which, however, have proved ineffective in establishing a spectrum of context-dependent morphological phenotypes. Here, we have developed MorphOMICs, a topological data analysis approach to overcome feature-selection-based biases and biological variability. We extracted a spatially heterogeneous and sexually-dimorphic morphological phenotype for seven adult brain regions, with ovariectomized females forming their own distinct cluster. This sex-specific phenotype declines with maturation but increases over the disease trajectories in two neurodegeneration models, 5xFAD and CK-p25. Females show an earlier morphological shift in the immediately-affected brain regions. Finally, we demonstrate that both the primary- and the short terminal processes provide distinct insights to morphological phenotypes. MorphOMICs maps microglial morphology into a spectrum of cue-dependent phenotypes in a minimally-biased and semi-automatic way.

neuroscience↗

bioRxiv2018

Finding informative neurons in the brain using Multi-Scale Relevance

We propose a metric - called Multi-Scale Relevance (MSR) - to score neurons for their prominence in encoding for the animals behaviour that is being observed in a multi-electrode array recording experiment. The MSR assumes that relevant neurons exhibit a wide variability in their dynamical state, in response to the external stimulus, across different time scales. It is a non-parametric, fully featureless indicator, in that it uses only the time stamps of the firing activity, without resorting to any a priori covariate or invoking any specific tuning curve for neural activity. We test the method on data from freely moving rodents, where we found that neurons having low MSR tend to have low mutual information and low firing sparsity across the correlates that are believed to be encoded by the region of the brain where the recordings were made. In addition, neurons with high MSR contain significant information on spatial navigation and allow to decode spatial position or head direction as efficiently as those neurons whose firing activity has high mutual information with the covariate to be decoded.

neuroscience↗