Multiple particle tracking analysis in isolated nuclei reveals the mechanical phenotype of leukemia cells

Abstract The nucleus is fundamentally composed by lamina and nuclear membranes that enclose the chromatin, nucleoskeletal components and suspending nucleoplasm. The functional connections of this network integrate external stimuli into cell signals, including physical forces to mechanical responses...

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Main Authors: Diego Herráez-Aguilar, Elena Madrazo, Horacio López-Menéndez, Manuel Ramírez, Francisco Monroy, Javier Redondo-Muñoz
Format: Article
Language:English
Published: Nature Portfolio 2020-04-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-020-63682-5
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author Diego Herráez-Aguilar
Elena Madrazo
Horacio López-Menéndez
Manuel Ramírez
Francisco Monroy
Javier Redondo-Muñoz
author_facet Diego Herráez-Aguilar
Elena Madrazo
Horacio López-Menéndez
Manuel Ramírez
Francisco Monroy
Javier Redondo-Muñoz
author_sort Diego Herráez-Aguilar
collection DOAJ
description Abstract The nucleus is fundamentally composed by lamina and nuclear membranes that enclose the chromatin, nucleoskeletal components and suspending nucleoplasm. The functional connections of this network integrate external stimuli into cell signals, including physical forces to mechanical responses of the nucleus. Canonically, the morphological characteristics of the nucleus, as shape and size, have served for pathologists to stratify and diagnose cancer patients; however, novel biophysical techniques must exploit physical parameters to improve cancer diagnosis. By using multiple particle tracking (MPT) technique on chromatin granules, we designed a SURF (Speeded Up Robust Features)-based algorithm to study the mechanical properties of isolated nuclei and in living cells. We have determined the apparent shear stiffness, viscosity and optical density of the nucleus, and how the chromatin structure influences on these biophysical values. Moreover, we used our MPT-SURF analysis to study the apparent mechanical properties of isolated nuclei from patients of acute lymphoblastic leukemia. We found that leukemia cells exhibited mechanical differences compared to normal lymphocytes. Interestingly, isolated nuclei from high-risk leukemia cells showed increased viscosity than their counterparts from normal lymphocytes, whilst nuclei from relapsed-patient's cells presented higher density than those from normal lymphocytes or standard- and high-risk leukemia cells. Taken together, here we presented how MPT-SURF analysis of nuclear chromatin granules defines nuclear mechanical phenotypic features, which might be clinically relevant.
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spelling doaj.art-f251fc62450d4b088f3d2148df2eeecc2022-12-21T20:34:13ZengNature PortfolioScientific Reports2045-23222020-04-0110111210.1038/s41598-020-63682-5Multiple particle tracking analysis in isolated nuclei reveals the mechanical phenotype of leukemia cellsDiego Herráez-Aguilar0Elena Madrazo1Horacio López-Menéndez2Manuel Ramírez3Francisco Monroy4Javier Redondo-Muñoz5Department of Physical Chemistry, Complutense UniversityDepartment of Immunology, Hospital 12 de Octubre Health Research Institute (imas12), School of Medicine, Complutense UniversityDepartment of Physical Chemistry, Complutense UniversityOncolohematology. Hospital Universitario Niño JesúsDepartment of Physical Chemistry, Complutense UniversityDepartment of Immunology, Hospital 12 de Octubre Health Research Institute (imas12), School of Medicine, Complutense UniversityAbstract The nucleus is fundamentally composed by lamina and nuclear membranes that enclose the chromatin, nucleoskeletal components and suspending nucleoplasm. The functional connections of this network integrate external stimuli into cell signals, including physical forces to mechanical responses of the nucleus. Canonically, the morphological characteristics of the nucleus, as shape and size, have served for pathologists to stratify and diagnose cancer patients; however, novel biophysical techniques must exploit physical parameters to improve cancer diagnosis. By using multiple particle tracking (MPT) technique on chromatin granules, we designed a SURF (Speeded Up Robust Features)-based algorithm to study the mechanical properties of isolated nuclei and in living cells. We have determined the apparent shear stiffness, viscosity and optical density of the nucleus, and how the chromatin structure influences on these biophysical values. Moreover, we used our MPT-SURF analysis to study the apparent mechanical properties of isolated nuclei from patients of acute lymphoblastic leukemia. We found that leukemia cells exhibited mechanical differences compared to normal lymphocytes. Interestingly, isolated nuclei from high-risk leukemia cells showed increased viscosity than their counterparts from normal lymphocytes, whilst nuclei from relapsed-patient's cells presented higher density than those from normal lymphocytes or standard- and high-risk leukemia cells. Taken together, here we presented how MPT-SURF analysis of nuclear chromatin granules defines nuclear mechanical phenotypic features, which might be clinically relevant.https://doi.org/10.1038/s41598-020-63682-5
spellingShingle Diego Herráez-Aguilar
Elena Madrazo
Horacio López-Menéndez
Manuel Ramírez
Francisco Monroy
Javier Redondo-Muñoz
Multiple particle tracking analysis in isolated nuclei reveals the mechanical phenotype of leukemia cells
Scientific Reports
title Multiple particle tracking analysis in isolated nuclei reveals the mechanical phenotype of leukemia cells
title_full Multiple particle tracking analysis in isolated nuclei reveals the mechanical phenotype of leukemia cells
title_fullStr Multiple particle tracking analysis in isolated nuclei reveals the mechanical phenotype of leukemia cells
title_full_unstemmed Multiple particle tracking analysis in isolated nuclei reveals the mechanical phenotype of leukemia cells
title_short Multiple particle tracking analysis in isolated nuclei reveals the mechanical phenotype of leukemia cells
title_sort multiple particle tracking analysis in isolated nuclei reveals the mechanical phenotype of leukemia cells
url https://doi.org/10.1038/s41598-020-63682-5
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