Biology subjects

Tesei, A.

Publications and source records attributed to Tesei, A..

2 recordsLinked to original sources

bioRxiv2022

CometAnalyser: a user-friendly, open-source deep-learning microscopy tool for quantitative comet assay analysis.

Comet assay provides an easy solution to estimate DNA damage in single cells through microscopy assessment. It is widely used in the analysis of genotoxic damages induced by radiotherapy or chemotherapeutic agents. DNA damage is quantified at the single-cell level by computing the displacement between the genetic material within the nucleus, typically called "comet head", and the genetic material in the surrounding part of the cell, considered as the "comet tail". Today, the number of works based on Comet Assay analyses is really impressive. In this work, besides revising the solutions available to obtain reproducible and reliable quantitative data, we developed an easy-to-use tool named CometAnalyser. It is designed for the analysis of both fluorescent and silver-stained wide-field microscopy images and allows to automatically segment and classify the comets, besides extracting Tail Moment and several other intensity/morphological features for performing statistical analysis. CometAnalyser is an open-source deep-learning tool. It works with Windows, Macintosh, and UNIX-based systems. Source code, standalone versions, user manual, sample images, video tutorial and further documentation are freely available at: https://sourceforge.net/p/cometanalyser. HIGHLIGHTSO_LIComet assay provides an easy solution to estimate DNA damage in single cells. C_LIO_LIToday, an impressive number of works are based on Comet Assay analyses, especially in the field of cancer research. C_LIO_LIComet assay was originally performed as a qualitative analysis. C_LIO_LINone of the free tools today available work on both fluorescent- and silver-stained images. C_LIO_LIWe developed CometAnalyser, an open-source deep-learning tool designed for easy segmentation and classification of comets in fluorescent- and silver-stained images. C_LI

bioengineering↗

bioRxiv2020

Patient-derived glioblastoma cells (GBM) exhibit distinct biomechanical profiles associated with altered activity in the cytoskeleton regulatory pathway

Glioblastoma multiforme (GBM) is the most commonly diagnosed brain cancer in adults, characterized by rapid proliferation and aggressive invasion into the stroma. Advances in our understanding of the molecular subtypes of GBM have provided attractive druggable targets. However, the high degree of heterogeneity both among patients and within individual tumors has proven a significant challenge for the development of effective therapies. We hypothesized that this heterogeneity is also represented in the mechanical phenotypes of GBM, as the physical properties of tumor tissue strongly influence elements of tumor progression including cell cycle regulation, migration, and therapeutic resistance. To assess these phenotypes, we employed optical trap-based active microrheology to determine the viscoelastic properties of patient-derived GBM cells in 3D hydrogels mimicking the brain ECM. We found that each GBM cell line had a distinct rheological profile as a function of treatment status, and cell lines could be further characterized by strong power law dependence describing intracellular viscoelastic behavior. Single-cell phenotyping according to power law dependence was able to identify subpopulations of cells within the treatment-resistant line. Finally, proteomic analysis indicated that altered mechanical profiles were associated with differential cytoskeletal regulation, particularly in actin - and myosin-binding pathways. This work suggests that evaluating mechanical properties may serve as a valuable strategy for the further stratification of these tumors, and encourages the investigation of cytoskeleton regulation as a potential therapeutic target for GBM.

biophysics↗