Comparison of the internucleotide interval statistics with the DNA walk analysis: (a) DFA fluctuation functions of the internucleotide intervals (full lines) and of the DNA walks (dashdot lines) and (b) the ACFs of the inter-nucleotide intervals (full lines), all provided for the DNA sequences of <i>H. Sapiens</i> (upper curves in each panel) and <i>Bacteria</i> (lower curves in each panel) full genomes.

<p>For the internucleotide interval sequences, the arguments are multiplied by the average interval to provide all results in the same units of base pairs. Vertical dashed lines refer to the approximate boundaries of characteristic scaling regimes for different hierarchical levels of eukaryotic DNA packaging structure (exemplified for <i>H. Sapiens</i>, following <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0112534#pone.0112534-Arneodo1" target="_blank">[2]</a>).</p

PDFs of the inter-nucleotide intervals A-A, T-T (open symbols); G-G, C-C (full symbols) in the DNA sequences from <i>Archaea</i> () (48 species), <i>Bacteria</i> () (72 species) and <i>H. Sapiens</i> () (22 chromosomes).

<p>For comparison, dotted lines show corresponding exponential PDFs. The inset shows the size distribution plots of the DNA sequences considered.</p

PDFs of the internucleotide intervals in the DNA from full genomes of ten different organisms at different evolutionary positions from <i>Archaea</i> and <i>Bacteria</i> to <i>H. Sapiens</i>.

<p>The thin dashed line shows an approximation by a single -exponential, while the thick dashed line shows an approximation by a sum of two -exponentials. For comparison, the dotted line shows the corresponding exponential PDF. The inset shows the evolution of the average interval separately for strongly (G:C) and weakly (A:T) bonded nucleotides.</p

PDFs of the internucleotide intervals in the DNA from full genomes of <i>Bacteria</i> classified into four groups according to the fraction of G and C in their genomes (GC-content) and <i>Archaea</i> classified into three groups according to their optimal living temperature, from normal environment to extermophiles.

<p>The dashed lines show approximations by a single -exponential with for <i>Bacteria</i> and for <i>Archaea</i>. Open symbols denote distributions for A and T, while full symbols denote distributions for G and C.</p

Similar to Fig. 3 but shows the corresponding PDFs for the transcribed DNA () and for the complementary DNA (cDNA, ).

<p>Fits are the same as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0112534#pone-0112534-g003" target="_blank">Fig. 3</a>. To avoid overlapping, the PDFs for <i>Bacteria</i> are shifted downwards by two decades. For comparison, dotted lines show corresponding exponential PDFs.</p

Fast and simple tool for the quantification of biofilm-embedded cells sub-populations from fluorescent microscopic images

<div><p>Fluorescent staining is a common tool for both quantitative and qualitative assessment of pro- and eukaryotic cells sub-population fractions by using microscopy and flow cytometry. However, direct cell counting by flow cytometry is often limited, for example when working with cells rigidly adhered either to each other or to external surfaces like bacterial biofilms or adherent cell lines and tissue samples. An alternative approach is provided by using fluorescent microscopy and confocal laser scanning microscopy (CLSM), which enables the evaluation of fractions of cells subpopulations in a given sample. For the quantitative assessment of cell fractions in microphotographs, we suggest a simple two-step algorithm that combines single cells selection and the statistical analysis. To facilitate the first step, we suggest a simple procedure that supports finding the balance between the detection threshold and the typical size of single cells based on objective cell size distribution analysis. Based on a series of experimental measurements performed on bacterial and eukaryotic cells under various conditions, we show explicitly that the suggested approach effectively accounts for the fractions of different cell sub-populations (like the live/dead staining in our samples) in all studied cases that are in good agreement with manual cell counting on microphotographs and flow cytometry data. This algorithm is implemented as a simple software tool that includes an intuitive and user-friendly graphical interface for the initial adjustment of algorithm parameters to the microphotographs analysis as well as for the sequential analysis of homogeneous series of similar microscopic images without further user intervention. The software tool entitled <i>BioFilmAnalyzer</i> is freely available online at <a href="https://bitbucket.org/rogex/biofilmanalyzer/downloads/" target="_blank">https://bitbucket.org/rogex/biofilmanalyzer/downloads/</a>.</p></div

Evaluation of the <i>B</i>. <i>subtilis</i> biofilm-embedded non-viable cells fraction by using <i>BioFilmAnalyzer</i> software exemplified for 12 microscopic images.

<p>The percentage of red-stained cells quantified by the <i>BioFilmAnalyzer</i> software is shown in each panel.</p

Consecutive steps in cell quantification by <i>BioFilmAnalyzer</i>.

<p>(A) original image containing overlapped red and green channels, (B) selected red channel data after threshold-based filtering, (C) selected cells of size between <i>s</i>_min and <i>s</i>_max that are used to determine the effective single cell size with each separate cell shown by another color as determined by the automatic segmentation algorithm.</p

Evaluation of the Caco-2 non-viable cells fraction by using <i>BioFilmAnalyzer</i> software exemplified for 12 microscopic images.

<p>The percentage of red-stained cells quantified by the <i>BioFilmAnalyzer</i> software is shown in each panel.</p

The live/dead ratio dependencies for different image analysis thresholds <i>T</i>.

<p>Full lines show the linear regression lines, while dashed line shows the ideal counting line as determined by the manual analysis performed by several experts in visual microscopic image analysis. Four confocal images containing between 12 and 23 Z-stacks were taken for the analysis, before and after being subjected to either Gaussian or Sobel filtering, as indicated.</p