Biology subjects

Zapperi, S.

Publications and source records attributed to Zapperi, S..

5 recordsLinked to original sources

bioRxiv2023

Gene regulatory programs in the life history of Salpingoeca rosetta

The choanoflagellate Salpingoeca rosetta can differentiate into at least five morphologically and behaviorally distinct cell types during its lifetime, going from individual motile cells to linear and rosette-shaped colonies. Due to the capability to form colonies and its close relationship with Metazoa, this organism is considered a model for studying multicellular evolution. The gene regulatory programs underlying these transformations are, however, unknown. Here we analyze transcriptomic data obtained from Salpingoeca rosetta in different states to identify a core of genes associated with the formation of multicellular colonies. We then compare the results with other organisms which display simple forms of multicellularity, highlighting commonalities and differences.

evolutionary biology↗

bioRxiv2022

Infiltration of Tumor Spheroids by Activated Immune Cells

Recent years have seen a tremendous growth of interest in understanding the role that the adaptive immune system could play in interdicting tumor progression. In this context, it has been shown that the density of adaptive immune cells inside a solid tumor serves as a favorable prognostic marker across different types of cancer. The exact mechanisms underlying the degree of immune cell infiltration is largely unknown. Here, we quantify the temporal dynamics of the density profile of activated immune cells around a solid tumor spheroid. We propose a computational model incorporating immune cells with active, persistent movement and a proliferation rate that depends on the presence of cancer cells, and show that the model able to reproduce quantitatively the experimentally measured infiltration profile. Studying the density distribution of immune cells inside a solid tumor can help us better understand immune trafficking in the tumor micro-environment, hopefully leading towards novel immunotherapeutic strategies.

cancer biology↗

bioRxiv2021

Spatial organization of nuclear pores in Xaenopus laevis oocytes

Nuclear pores are protein assemblies inserted in the nuclear envelope of eukaryotic cells, acting as main gates for communication between nucleus and cytoplasm. So far, nuclear pores have been extensively studied to determine their structure and composition, yet their spatial organization and geometric arrangement on the nuclear surface are still poorly understood. Here, we analyze super-resolution images of the surface of Xenopus laevis oocyte nuclei during development, and characterize the arrangement of nuclear pores using tools commonly employed to study the atomic structural and topological features of soft matter. To interpret the experimental results, we hypothesize an effective interaction among nuclear pores and implemented it in extensive numerical simulations of octagonal clusters mimicking typical pore shapes. Thanks to our simple model, we find simulated spatial distributions of nuclear pores that are in excellent agreement with experiments, suggesting that an effective interaction among nuclear pores exists and could explain their geometrical arrangement. Furthermore, our results show that the statistical features of the geometric arrangement of nuclear pores do not depend on the type of pore-pore interaction, attractive or repulsive, but are mainly determined by the octagonal symmetry of each single pore. These results pave the way to further studies needed to determine the biological nature of pore-pore interactions.

biophysics↗

bioRxiv2019

Identifying inhibitors of epithelial-mesenchymal plasticity using a network topology based approach

Metastasis is the cause of over 90% of cancer-related deaths. Cancer cells undergoing metastasis can switch dynamically between different phenotypes, enabling them to adapt to harsh challenges such as overcoming anoikis and evading immune response. This ability, known as phenotypic plasticity, is crucial for the survival of cancer cells during metastasis, as well as acquiring therapy resistance. Various biochemical networks have been identified to contribute to phenotypic plasticity, but how plasticity emerges from the dynamics of these networks remains elusive. Here, we investigated the dynamics of various regulatory networks implicated in Epithelial-Mesenchymal Plasticity (EMP) - an important arm of phenotypic plasticity - through two different mathematical modelling frameworks: a discrete, parameter-independent framework (Boolean) and a continuous, parameter-agnostic modelling framework (RACIPE). Results from either framework in terms of phenotypic distributions obtained from a given EMP network are qualitatively similar and suggest that these networks are multi-stable and can give rise to phenotypic plasticity. Neither method requires specific kinetic parameters, thus our results emphasize that EMP can emerge through these networks over a wide range of parameter sets, elucidating the importance of network topology in enabling phenotypic plasticity. Furthermore, we show that the ability to exhibit phenotypic plasticity correlates positively with the number of positive feedback loops in a given network. These results pave a way towards an unorthodox network topology-based approach to identify crucial links in a given EMP network that can reduce phenotypic plasticity and possibly inhibit metastasis - by reducing the number of positive feedback loops.

systems biology↗

bioRxiv2017

Is obesity a genetic disease? Human obese transcriptome analysis in monozygotic twins

Obesity is a pandemic disease with a critical increase in childhood. An important unanswered question is to understand if this disease is due to genetic causes or to the life-style of the subjects. To address this question, we have analyzed if monozygotic twins show the same robust transcriptomic signature (5{sigma}, as for the Higgs Boson) that we have recently revealed in obese subjects. Our results show that our signature correlates with BMI in paired transcriptomes of monozygotic twins, suggesting that the signature does not reflect underlying genetic causes.

systems biology↗