Biology subjects

Mollo, V.

Publications and source records attributed to Mollo, V..

3 recordsLinked to original sources

bioRxiv2023

Kirigami electronics for long-term electrophysiological recording of human neural organoids and assembloids

Organoids and assembloids have emerged as a promising platform to model aspects of nervous system development. Longterm, minimally-invasive recordings in these multi-cellular systems are essential for developing disease models. Current technologies, such as patch-clamp, penetrating microelectrodes, planar electrode arrays and substrate-attached flexible electrodes, do not, however, allow chronic recording of organoids in suspension, which is necessary to preserve their architecture. Inspired by the art of kirigami, we developed flexible electronics that transition from a 2D pattern to a 3D basketlike configuration to accommodate the long-term culture of organoids in suspension. This platform, named kirigami electronics (KiriE), integrates with and enables chronic recording of cortical organoids while preserving morphology, cytoarchitecture, and cell composition. KiriE can be integrated with optogenetic and pharmacological stimulation and model disease. Moreover, KiriE can capture activity in cortico-striatal assembloids. Moving forward, KiriE could reveal disease phenotypes and activity patterns underlying the assembly of the nervous system.

neuroscience↗

bioRxiv2023

IN VIVO ISOLATION OF A QUIESCENT MELANOMA POPULATION WITH INVASIVE PROPERTIES UNVEILS A TRANSCRIPTIONAL REPROGRAMMING DRIVEN BY THE TUMOR NICHE

Melanoma is a heterogeneous tumor composed of many interacting cellular populations and highly plastic melanoma cells that pass through distinct cell states to adapt to the surrounding microenvironment. Slow cycling is a transient state that defines a minor population of cells with cancer-initiating features. These cells are enriched upon drug therapy and can trigger cancer relapse and metastasis dissemination when they acquire proliferative potential. This population is still not entirely characterized. Here we provide evidence of the existence of a slow cycling melanoma population isolated in vivo from melanoma PDXs using the H2B-GFP system. These cells display a highly invasive phenotype and are able to dynamically respond to cancer microenvironmental stimuli. Single cell transcriptomic analysis unveils a significant transcriptional heterogeneity of GFP-retaining slow cycling cells, defining a quiescent subpopulation of cells. These cells show a different phenotype in primary tumors and matched metastases, suggesting that tumor niche pressure drives a transcriptional reprogramming of quiescent cells during melanoma progression.

cancer biology↗

bioRxiv2018

Nanoscale investigation in 3D scaffolds of cell-material interactions for tissue-engineering

Cell fate is largely determined by interactions that occur at the interface between cells and their surrounding microenvironment. For this reason, especially in the field of cell- and tissue-engineering, there is a growing interest in developing characterization techniques that allow a deep evaluation of cell-material interaction at the nanoscale, particularly focusing on cell adhesion processes. While for 2D culturing systems a consolidated series of tools already satisfy this need, in 3D environments, more closely recapitulating complex in vivo structures, there is still a lack of procedure furthering the comprehension of cell-material interactions. Here, we report for the first time the use of a SEM/FIB system for the characterization of cellular adhesion in 3D scaffolds fabricated by means of different techniques. Our results clearly show the capability of the developed approach to finely resolve both scaffold-cells interface and nanometer scale features of cell bodies involved in the upregulation of cellular behavior. These results are relevant for studying cellular guidance strategies and for the consequent design of more efficient cell-instructive platforms for tissue-engineering applications as well as for in vitro 3D models.

bioengineering↗