Detection and Segmentation of Nucleoids Based on Gradient Path Labelling João Santinha, André D. Mora and José Fonseca Computational Intelligence Research Group (CA3), UNINOVA – Centre of Technology and Systems, Caparica, Portugal Email: {jsantinha, atm, jmf}@uninova.pt Nádia Gonçalves and Andre S. Ribeiro Laboratory of Biosystem Dynamics – Department of Signal Processing, Tampere University of Technology, Tampere, Finland Email: {nadia.moreiragoncalves, andre.ribeiro}@tut.fi Abstract—Cellular aging is one of the topics that live cell imaging can assist. With age, there is an increase of aggregates of misfolded proteins, to which age-related diseases have been linked to. In Escherichia coli, protein aggregates linked to its aging process exhibit a spatial distribution that appears to be caused by the nucleoid at midcell. To correlate the locations of protein aggregates and the nucleoid, it is necessary to detect and segment the nucleoid from microscopy images. We present an adaptation of methods for Drusens’ detection and segmentation to nucleoids in E. coli. The size of the nucleoid, extracted using the method here proposed, was compared with an alternative measure (FWHM-based measure) and with the regions of anisotropies in aggregates motions. These comparisons suggest that our new method is of use, providing more accurate minor axis lengths. Also, it provides additional measures, such as the nucleoid’s center orientation angle, area, and pixel list. Index Terms—Escherichia coli, cellular aging, nucleoid detection, nucleoid segmentation I. INTRODUCTION Ageing is an important topic in current live cell microscopy studies. While it is a fundamental characteristic of any living system, its underlying principles remain mysterious [1]. It has been established that one of its consequences, namely the accumulation of aggregates of misfolded proteins, is a likely cause of age- related diseases (e.g., Huntington’s, Alzheimer’s, spongiform encephalopathies, Parkinson’s, and cataracts) [1], [2]. Recent studies have conducted microscopy observations of unicellular models with the aim of revealing the underlying mechanisms related to cellular ageing processes [1]. The use of Escherichia coli as a model organism, has elucidated much facts on the process of protein aggregation in this bacterium and promises significant advances in our understanding of cellular Manuscript received January 28, 2015; revised April 1, 2015. aging [1], [2]. The emergence of “aged” cells in E. coli populations has been linked to the accumulation of protein aggregates at the older pole of the aged bacterium [1]. The protein aggregates appear to be deposited at the poles, which, combined with cell division, results in asymmetric damage inheritance [2], [3]. The preference of the protein aggregates to locate at the cell poles has been attributed to macromolecular crowding [1], [4]. The macromolecular crowding is a consequence of the presence of the nucleoid, where the 4.6 kilobases (kb) genome DNA of Escherichia coli locates [5]. The DNA forms nucleoprotein complexes with at least 10 major DNA-binding proteins, including the DNA polymerases, the proteins involved in recombination and repair of DNA, and RNA polymerases, along with about 100 species of transcription factors that are associated with the nucleoid at some points in time [6] [7]. To study the effects of macromolecular crowding on the heterogeneous spatial distribution of the protein aggregates, it is advantageous to detect the aggregates and the nucleoids simultaneously, so as to correlate their spatial location. This can be achieved by fluorescent tagging. Even though, with this method, neither the nucleoids nor aggregate ‘spots’ have clear borders, it is necessary to perform their segmentation in order to establish spatial correlations. As the nucleoid segmentation is hampered by lack of nucleoid borders, contour-based segmentation methods cannot be used. However, recent studies indicate that the Gaussian function can be implemented as the Point Spread Function (PSF) model, for fitting the position of a fluorescent emitter in a cell [8]. Here, we propose an adaptation of a method previously used in automatic Drusen detection in retinal images [9] to the detection and segmentation of nucleoids and we demonstrate its applicability on images of cells at different temperatures, which causes nucleoid structures to differ, e.g., in size and positioning. International Journal of Pharma Medicine and Biological Sciences Vol. 4, No. 1, January 2015 ©2015 Int. J. Pharm. Med. Biol. Sci. 51