Deciphering the internal complexity of living cells with quantitative phase microscopy: a multiscale approach.
The distribution of refractive indices (RIs) of a living cell contributes in a nonintuitive manner to its optical phase image and quite rarely can be inverted to recover its internal structure. The interpretation of the quantitative phase images of living cells remains a difficult task because (1) we still have very little knowledge on the impact of its internal macromolecular complexes on the local RI and (2) phase changes produced by light propagation through the sample are mixed with diffraction effects by the internal cell bodies. We propose to implement a two-dimensional wavelet-based contour chain detection method to distinguish internal boundaries based on their greatest optical path difference gradients. These contour chains correspond to the highest image phase contrast and follow the local RI inhomogeneities linked to the intracellular structural intricacy. Their statistics and spatial distribution are the morphological indicators suited for comparing cells of different origins and/or to follow their transformation in pathologic situations. We use this method to compare nonadherent blood cells from primary and laboratory culture origins and to assess the internal transformation of hematopoietic stem cells by the transduction of the BCR-ABL oncogene responsible for the chronic myelogenous leukemia.
CNRS UMR5672, Laboratoire de Physique, Ecole Normale Supérieure de Lyon, 46 Allée d'Italie, 69007 Lyon, FrancebUniversité de Lyon 1, 43 Boulevard du 11 Novembre 1918, 69100 Villeurbanne, France.
Cristina
C
Martinez-Torres
CNRS UMR5672, Laboratoire de Physique, Ecole Normale Supérieure de Lyon, 46 Allée d'Italie, 69007 Lyon, FrancebUniversité de Lyon 1, 43 Boulevard du 11 Novembre 1918, 69100 Villeurbanne, FrancecCNRS UMR5286, INSERM U1052, Centre de Recherche en Cancérolog.
Bastien
B
Laperrousaz
Université de Lyon 1, 43 Boulevard du 11 Novembre 1918, 69100 Villeurbanne, FrancedCNRS USR3010, Laboratoire Joliot-Curie, Ecole Normale Supérieure de Lyon, 46 Allée d'Italie, 69007 Lyon, France.
Lotfi
L
Berguiga
CNRS UMR5672, Laboratoire de Physique, Ecole Normale Supérieure de Lyon, 46 Allée d'Italie, 69007 Lyon, FrancebUniversité de Lyon 1, 43 Boulevard du 11 Novembre 1918, 69100 Villeurbanne, France.
Elise
E
Boyer-Provera
CNRS UMR5248, Institut de Chimie et Biologie des Membranes et des Nano-objets, Allée de Geoffroy St Hilaire, 33600 Pessac, France.
Juan
J
Elezgaray
Université de Lyon 1, 43 Boulevard du 11 Novembre 1918, 69100 Villeurbanne, FrancecCNRS UMR5286, INSERM U1052, Centre de Recherche en Cancérologie de Lyon, 28 rue Laennec, 69008 Lyon, FrancefHospices Civils de Lyon, Hematology Department, Centre Hospitali.
Franck E
FE
Nicolini
Université de Lyon 1, 43 Boulevard du 11 Novembre 1918, 69100 Villeurbanne, FrancecCNRS UMR5286, INSERM U1052, Centre de Recherche en Cancérologie de Lyon, 28 rue Laennec, 69008 Lyon, France.
Veronique
V
Maguer-Satta
CNRS UMR5672, Laboratoire de Physique, Ecole Normale Supérieure de Lyon, 46 Allée d'Italie, 69007 Lyon, FrancebUniversité de Lyon 1, 43 Boulevard du 11 Novembre 1918, 69100 Villeurbanne, France.
Alain
A
Arneodo
CNRS UMR5672, Laboratoire de Physique, Ecole Normale Supérieure de Lyon, 46 Allée d'Italie, 69007 Lyon, FrancebUniversité de Lyon 1, 43 Boulevard du 11 Novembre 1918, 69100 Villeurbanne, France.
Françoise
F
Argoul
D000465:Algorithms; D002460:Cell Line; D004912:Erythrocytes / Q000166:cytology; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D042541:Intracellular Space / Q000502:physiology*; D008858:Microscopy, Phase-Contrast / Q000379:methods*; D012815:Signal Processing, Computer-Assisted; D059010:Single-Cell Analysis / Q000379:methods*