NeuriTES. Monitoring neurite changes through transfer entropy and semantic segmentation in bright-field time-lapse microscopy
Arianna Mencattini,
Alida Spalloni,
Paola Casti,
Maria Colomba Comes,
Davide Di Giuseppe,
Gianni Antonelli,
Michele D'Orazio,
Joanna Filippi,
Francesca Corsi,
Hervé Isambert,
Corrado Di Natale,
Patrizia Longone,
Eugenio Martinelli
Affiliations
Arianna Mencattini
Department of Electronic Engineering, University of Rome Tor Vergata, 00133 Rome, Italy; Interdisciplinary Center for Advanced Studies on Lab-on-Chip and Organ-on-Chip Applications (ICLOC), University of Rome Tor Vergata, 00133 Rome, Italy
Alida Spalloni
Molecular Neurobiology Unit, Fondazione Santa Lucia-IRCCS, Via Ardeatina, 306/354, 00179 Rome, Italy
Paola Casti
Department of Electronic Engineering, University of Rome Tor Vergata, 00133 Rome, Italy; Interdisciplinary Center for Advanced Studies on Lab-on-Chip and Organ-on-Chip Applications (ICLOC), University of Rome Tor Vergata, 00133 Rome, Italy
Maria Colomba Comes
Department of Electronic Engineering, University of Rome Tor Vergata, 00133 Rome, Italy; Interdisciplinary Center for Advanced Studies on Lab-on-Chip and Organ-on-Chip Applications (ICLOC), University of Rome Tor Vergata, 00133 Rome, Italy
Davide Di Giuseppe
Department of Electronic Engineering, University of Rome Tor Vergata, 00133 Rome, Italy; Interdisciplinary Center for Advanced Studies on Lab-on-Chip and Organ-on-Chip Applications (ICLOC), University of Rome Tor Vergata, 00133 Rome, Italy
Gianni Antonelli
Department of Electronic Engineering, University of Rome Tor Vergata, 00133 Rome, Italy; Interdisciplinary Center for Advanced Studies on Lab-on-Chip and Organ-on-Chip Applications (ICLOC), University of Rome Tor Vergata, 00133 Rome, Italy
Michele D'Orazio
Department of Electronic Engineering, University of Rome Tor Vergata, 00133 Rome, Italy; Interdisciplinary Center for Advanced Studies on Lab-on-Chip and Organ-on-Chip Applications (ICLOC), University of Rome Tor Vergata, 00133 Rome, Italy
Joanna Filippi
Department of Electronic Engineering, University of Rome Tor Vergata, 00133 Rome, Italy; Interdisciplinary Center for Advanced Studies on Lab-on-Chip and Organ-on-Chip Applications (ICLOC), University of Rome Tor Vergata, 00133 Rome, Italy
Francesca Corsi
Interdisciplinary Center for Advanced Studies on Lab-on-Chip and Organ-on-Chip Applications (ICLOC), University of Rome Tor Vergata, 00133 Rome, Italy
Hervé Isambert
Institut Curie - Centre de Recherche, CNRS-UMR168 11, rue P. et M. Curie, 75005 Paris, France
Corrado Di Natale
Department of Electronic Engineering, University of Rome Tor Vergata, 00133 Rome, Italy
Patrizia Longone
Molecular Neurobiology Unit, Fondazione Santa Lucia-IRCCS, Via Ardeatina, 306/354, 00179 Rome, Italy
Eugenio Martinelli
Department of Electronic Engineering, University of Rome Tor Vergata, 00133 Rome, Italy; Interdisciplinary Center for Advanced Studies on Lab-on-Chip and Organ-on-Chip Applications (ICLOC), University of Rome Tor Vergata, 00133 Rome, Italy; Corresponding author
Summary: One of the most challenging frontiers in biological systems understanding is fluorescent label-free imaging. We present here the NeuriTES platform that revisits the standard paradigms of video analysis to detect unlabeled objects and adapt to the dynamic evolution of the phenomenon under observation. Object segmentation is reformulated using robust algorithms to assure regular cell detection and transfer entropy measures are used to study the inter-relationship among the parameters related to the evolving system. We applied the NeuriTES platform to the automatic analysis of neurites degeneration in presence of amyotrophic lateral sclerosis (ALS) and to the study of the effects of a chemotherapy drug on living prostate cancer cells (PC3) cultures. Control cells have been considered in both the two cases study. Accuracy values of 93% and of 92% are achieved, respectively. NeuriTES not only represents a tool for investigation in fluorescent label-free images but demonstrates to be adaptable to individual needs. The bigger picture: One of the most challenging frontiers for the automatic understanding of biological systems is fluorescent label-free imaging in which the behavior changes of living being are characterized without cell staining. To this aim, we present here the NeuriTES platform that revisits standard paradigms of video analysis to detect unlabeled objects and correlate the analysis to phenotype evolution of the mechanisms under observation. Through the exploitation of adaptive algorithms and of transfer entropy measures, the platform assures regular cell detection and the possibility to extract reliable parameters related to the evolving cell system. As a proof-of-concept, NeuriTES is applied to two fascinating phenotype investigation scenarios, amyotrophic lateral sclerosis (ALS) disease mechanism and the study of the effects of a chemotherapy drug on living prostate cancer cells (PC3) cultures. Directed graphs assist the biologists with a visual understanding of the mechanisms identified.
