Діагностична значимість полярізаційно-оптичних властивостей рогівки ока при патології внутрішньоочного тиску

Незважаючи на прогрес в методах лікування і діагностики, глаукома останніми роками стала головною причиною невиліковної сліпоти в розвинених країнах світу. За даними ВООЗ більше 67 млн. чоловік в світі хворіють на глаукому і до 2030 року ця цифра повинна подвоїтися. Підвищення внутрішньоочного тиску (ВОТ) є одною з основних клінічних ознак глаукомного процесу, реєстрація якого лежить в основі діагностики і вибору методу адекватного лікування. Практично всі існуючи в теперішній час методи виміру ВОТ засновані на різних впливах на око (вантажами, плунжерами або струменем повітря). Як було встановлено, результати таких вимірів ВОТ суттєво залежать від біомеханічних параметрів рогівки або ока

Cell age dependent concentration of Escherichia coli divisome proteins analyzed with ImageJ and ObjectJ

The rod-shaped Gram-negative bacterium Escherichia coli multiplies by elongation followed by binary fission. Longitudinal growth of the cell envelope and synthesis of the new poles are organized by two protein complexes called elongasome and divisome, respectively. We have analyzed the spatio-temporal localization patterns of many of these morphogenetic proteins by immunolabeling the wild type strain MC4100 grown to steady state in minimal glucose medium at 28°C. This allowed the direct comparison of morphogenetic protein localization patterns as a function of cell age as imaged by phase contrast and fluorescence wide field microscopy. Under steady state conditions the age distribution of the cells is constant and is directly correlated to cell length. To quantify cell size and protein localization parameters in 1000s of labeled cells, we developed ‘Coli-Inspector,’ which is a project running under ImageJ with the plugin ‘ObjectJ.’ ObjectJ organizes image-analysis tasks using an integrated approach with the flexibility to produce different output formats from existing markers such as intensity data and geometrical parameters. ObjectJ supports the combination of automatic and interactive methods giving the user complete control over the method of image analysis and data collection, with visual inspection tools for quick elimination of artifacts. Coli-inspector was used to sort the cells according to division cycle cell age and to analyze the spatio-temporal localization pattern of each protein. A unique dataset has been created on the concentration and position of the proteins during the cell cycle. We show for the first time that a subset of morphogenetic proteins have a constant cellular concentration during the cell division cycle whereas another set exhibits a cell division cycle dependent concentration variation. Using the number of proteins present at midcell, the stoichiometry of the divisome is discussed.MP was funded by a grant form the Netherlands Organization for Scientific Research (NWO-ALW VIDI 864.09.015), TB, JL, WV, MV, and PN were funded by the European Commission Contract HEALTH-F3-2009-223431 (DIVINOCELL). MV and PN were also funded by the Ministerio de Ciencia e Innovación, Spanish Government Grants BIO2008-04478-C03-01 and BIO2011-28941-C03-01. WV was also funded by a Wellcome Trust Senior Investigator Award (WT101824AIA).Peer reviewedPeer Reviewe

Different Amounts of DNA in Newborn Cells of Escherichia coli Preclude a Role for the Chromosome in Size Control According to the “Adder” Model

According to the recently-revived adder model for cell size control, newborn cells of Escherichia coli will grow and divide after having added a constant size or length, ΔL, irrespective of their size at birth. Assuming exponential elongation, this implies that large newborns will divide earlier than small ones. The molecular basis for the constant size increment is still unknown. As DNA replication and cell growth are coordinated, the constant ΔL could be based on duplication of an equal amount of DNA, ΔG, present in newborn cells. To test this idea, we measured amounts of DNA and lengths of nucleoids in DAPI-stained cells growing in batch culture at slow and fast rates. Deeply-constricted cells were divided in two subpopulations of longer and shorter lengths than average; these were considered to represent large and small prospective daughter cells, respectively. While at slow growth, large and small prospective daughter cells contained similar amounts of DNA, fast growing cells with multiforked replicating chromosomes, showed a significantly higher amount of DNA (20%) in the larger cells. This observation precludes the hypothesis that ΔL is based on the synthesis of a constant ΔG. Growth curves were constructed for siblings generated by asymmetric division and growing according to the adder model. Under the assumption that all cells at the same growth rate exhibit the same time between initiation of DNA replication and cell division (i.e., constant C+D-period), the constructions predict that initiation occurs at different sizes (Li) and that, at fast growth, large newborn cells transiently contain more DNA than small newborns, in accordance with the observations. Because the state of segregation, measured as the distance between separated nucleoids, was found to be more advanced in larger deeply-constricted cells, we propose that in larger newborns nucleoid separation occurs faster and at a shorter length, allowing them to divide earlier. We propose a composite model in which both differential initiation and segregation leads to an adder-like behavior of large and small newborn cells

Data_Sheet_1.PDF

<p>According to the recently-revived adder model for cell size control, newborn cells of Escherichia coli will grow and divide after having added a constant size or length, ΔL, irrespective of their size at birth. Assuming exponential elongation, this implies that large newborns will divide earlier than small ones. The molecular basis for the constant size increment is still unknown. As DNA replication and cell growth are coordinated, the constant ΔL could be based on duplication of an equal amount of DNA, ΔG, present in newborn cells. To test this idea, we measured amounts of DNA and lengths of nucleoids in DAPI-stained cells growing in batch culture at slow and fast rates. Deeply-constricted cells were divided in two subpopulations of longer and shorter lengths than average; these were considered to represent large and small prospective daughter cells, respectively. While at slow growth, large and small prospective daughter cells contained similar amounts of DNA, fast growing cells with multiforked replicating chromosomes, showed a significantly higher amount of DNA (20%) in the larger cells. This observation precludes the hypothesis that ΔL is based on the synthesis of a constant ΔG. Growth curves were constructed for siblings generated by asymmetric division and growing according to the adder model. Under the assumption that all cells at the same growth rate exhibit the same time between initiation of DNA replication and cell division (i.e., constant C+D-period), the constructions predict that initiation occurs at different sizes (Li) and that, at fast growth, large newborn cells transiently contain more DNA than small newborns, in accordance with the observations. Because the state of segregation, measured as the distance between separated nucleoids, was found to be more advanced in larger deeply-constricted cells, we propose that in larger newborns nucleoid separation occurs faster and at a shorter length, allowing them to divide earlier. We propose a composite model in which both differential initiation and segregation leads to an adder-like behavior of large and small newborn cells.</p

When Phase Contrast Fails: ChainTracer and NucTracer, Two ImageJ Methods for Semi-Automated Single Cell Analysis Using Membrane or DNA Staining

<div><p>Within bacterial populations, genetically identical cells often behave differently. Single-cell measurement methods are required to observe this heterogeneity. Flow cytometry and fluorescence light microscopy are the primary methods to do this. However, flow cytometry requires reasonably strong fluorescence signals and is impractical when bacteria grow in cell chains. Therefore fluorescence light microscopy is often used to measure population heterogeneity in bacteria. Automatic microscopy image analysis programs typically use phase contrast images to identify cells. However, many bacteria divide by forming a cross-wall that is not detectable by phase contrast. We have developed ‘ChainTracer’, a method based on the ImageJ plugin ObjectJ. It can automatically identify individual cells stained by fluorescent membrane dyes, and measure fluorescence intensity, chain length, cell length, and cell diameter. As a complementary analysis method we developed 'NucTracer', which uses DAPI stained nucleoids as a proxy for single cells. The latter method is especially useful when dealing with crowded images. The methods were tested with <i>Bacillus subtilis</i> and <i>Lactococcus lactis</i> cells expressing a GFP-reporter. In conclusion, ChainTracer and NucTracer are useful single cell measurement methods when bacterial cells are difficult to distinguish with phase contrast.</p></div

Microscopy images showing motile and non-motile <i>B</i>. <i>subtilis</i> cells during exponential growth in liquid medium.

<p>The <i>B</i>. <i>subtilis</i> strain (BSS339) contains the P_<i>hag</i><i>-gfp</i> reporter fusion. (A) Phase contrast, fluorescent membrane stain, and GFP images, respectively. Division septa, some indicated by red triangles, can be difficult to identify from phase contrast images. (B) ChainTracer screenshot showing straightened filaments. Filaments (<i>objects</i>) are numbered. An example of a line scan is shown as a dashed yellow arrow running through object #5, with resulting fluorescence intensity profile shown as a red graph underneath. Automatically detected peaks (septa) are indicated by red triangles over the intensity profile. (C) ChainTracer screenshot of the corresponding GFP channel. Automatically detected septa (<i>items</i>) are indicated by red triangles, manually added septa are indicated by blue triangles. The yellow boxes represent the two methods of fluorescence intensity data capture; a box encompassing an entire cell (cell #2 in filament #4) captures integrated GFP fluorescence, and a narrow box (cell #1 in filament #3) captures mean GFP measurement. (D-F) Summary of ObjectJ items making up an object in ChainTracer. (D) Cells shown in phase contrast, traced by a chain axis item (red), and bisected by a chain diameter (green) item. (E) Same cell as in D visualized in the membrane stain channel shows two cells, each bound by a cell box item (magenta), and an individual cell traced by a cell axis item (yellow dots). (F) Same cells as in D visualized in the GFP channel with cell box items (magenta). Scale bars are 5 μm.</p

Comparison of NucTracer with ChainTracer.

<p>The cumulative frequency graphs show the distribution of fluorescence intensities at time point 1 (Figs <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0151267#pone.0151267.g003" target="_blank">3C–3E</a> & <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0151267#pone.0151267.g005" target="_blank">5B</a>) using ChainTracer (green), ChainTracer with manual correction (black), NucTracer without manual correction (blue), and manual measured fluorescence intensities using ImageJ (red). Cumulative frequency graphs were obtained by summing up the relative cell numbers (frequencies) for increasing fluorescence intensities.</p