Multidimensional Scaling (MDS) plots from bacterial community composition observed in 72 sputum samples.

<p>Bubbles indicate relative abundances of the 4 most prevalent OTUs in the cohort: <i>P</i>. <i>aeruginosa</i> in green, <i>S</i>. <i>aureus</i> in orange, alpha-hemolytic <i>Streptococcus</i> (<i>Streptococcus</i> -1) in yellow, <i>R</i>. <i>mucilaginosa</i> in blue. 2D Stress values are given in each plot and reveal moderate stress. <b>(A)</b> Merged bubble plots from all four dominant OTUs, coloured bubbles indicating the individual abundances. <i>P</i>. <i>aeruginosa</i> as well as <i>S</i>. <i>aureus</i> have priority, whereas the abundances for <i>R</i>. <i>mucilaginosa</i> and alpha-hemolytic <i>Streptococcus</i> are in the background. (<b>B)</b> Individual MDS plots for each dominant OTU. Numbers indicate individual patients. Letters are according the order of sputum collection.</p

Comparison of prevalence of bacteria in the cohort identified by deep sequencing (NGS, grey bars) and cultivation for classical diagnostics (black bars).

<p>OTUs are listed on the left according their occurrence observed with deep sequencing. Bacteria present in >50% of all samples were categorized as highly prevalent, bacteria detectable in more than 10% of the cases were considered moderately prevalent and those observed in less than 10% of the cases were categorized as bacteria with low prevalence. Categorization follows detection rates by deep sequencing. For precise identification of bacteria see Table C in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0117436#pone.0117436.s001" target="_blank">S1 File</a>. Only 71 sputum samples were taken into account (no data from cultivation for sample #20B). * Streptococcus-1 was compared with alpha-hemolytic streptococci.</p

Multidimensional Scaling (MDS) plots from bacterial community composition observed in 72 sputum samples with superimposed host factors.

<p>For a better orientation in the plot, relative abundances of <i>S</i>. <i>aureus</i> are indicated as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0117436#pone.0117436.g001" target="_blank">Fig. 1B</a> (orange circles). <b>(A)</b> Age of patients superimposed on the previous MDS plot calculated for the community compositions of 72 sputum samples. Four age classes were defined for the cohort according to the statistical quartils. Symbols indicate the age of the patient at the time point of sputum collection. <b>(B)</b> Lung function of patients superimposed on the previous MDS plot defined for the community compositions of 72 sputum samples. Four classes of lung functions were calculated according to the statistical quartils of FEV₁ values measured for the patients on the day of sputum collection. Symbols indicate the four classes and samples without associated FEV₁ values. <b>(C)</b> CFTR mutations of patients superimposed on the previous MDS plot calculated for the community compositions of 72 sputum samples. Three classes of identified genotypes were determined for the cohort. Partly or completely unknown genotypes are accordingly labelled representing a fourth class.</p

Maximum relative abundances of the bacterial OTUs determined in individual sputum samples.

<p>Individual relative abundances were determined by deep sequencing. OTU identification was achieved by comparison with SSCP sequences.</p

Dynamics of community composition in three representative individuals (patient #20, #35 and #34) from the sub-cohort of patients that provided samples twice or three times.

<p>Each OTU is indicated by a specific colour and further identified in the figure legend. CF patients are identified by numbers and sputum sample are shown in chronological order, hereby, time intervals to the initial sample are indicated in the plot. All other OTUs summarized in grey represent low abundant species not represented by the taxa indicate in the figure.</p

DataSheet1_Qualitative and quantitative evaluation of computed tomography changes in adults with cystic fibrosis treated with elexacaftor-tezacaftor-ivacaftor: a retrospective observational study.docx

Introduction: The availability of highly effective triple cystic fibrosis transmembrane conductance regulator (CFTR) modulator combination therapy with elexacaftor–tezacaftor–ivacaftor (ETI) has improved pulmonary outcomes and quality of life of people with cystic fibrosis (pwCF). The aim of this study was to assess computed tomography (CT) changes under ETI visually with the Brody score and quantitatively with dedicated software, and to correlate CT measures with parameters of clinical response.Methods: Twenty two adult pwCF with two consecutive CT scans before and after ETI treatment initiation were retrospectively included. CT was assessed visually employing the Brody score and quantitatively by YACTA, a well-evaluated scientific software computing airway dimensions and lung parenchyma with wall percentage (WP), wall thickness (WT), lumen area (LA), bronchiectasis index (BI), lung volume and mean lung density (MLD) as parameters. Changes in CT metrics were evaluated and the visual and quantitative parameters were correlated with each other and with clinical changes in sweat chloride concentration, spirometry [percent predicted of forced expiratory volume in one second (ppFEV1)] and body mass index (BMI).Results: The mean (SD) Brody score improved with ETI [55 (12) vs. 38 (15); p 1 with the Brody score (r = −0.606, p = 0.003) and with WT (r = −0.538, p = 0.010).Discussion: Morphological treatment response to ETI can be assessed using the Brody score as well as quantitative CT parameters. Changes in CT correlated with clinical improvements. The quantitative analysis with YACTA proved to be an objective, reproducible and simple method for monitoring lung disease, particularly with regard to future interventional clinical trials.</p