MOESM3 of Functional analysis of granulocyte and monocyte subpopulations in neonates

Additional file 3: Figure S2. Gating strategy for oxidative burst setup. Representative probe of a new-born infant to measure oxidative burst. To clearly distinguish monocyte and granulocyte subpopulations FMOs for anti-CD14, −CD16 and -CD62L gating was used. Subsets were defined as already published by Pillay et al. (2012). CD16dim neutrophil population was distinguished by gating the 25th percentile of main neutrophil populatio

MOESM2 of Functional analysis of granulocyte and monocyte subpopulations in neonates

Additional file 2: Figure S1. A/B Gating strategy for granulocyte and monocyte subpopulations and their activation marker: Representative probe of a new-born infant for activation marker on granulocyte and monocyte subpopulation. After single cell gating and determination of living cells by ZOMBIE, cells were gated by SSC-A and subpopulation marker (CD14, CD16, CD62L) in their subpopulation according to FMOs. CD14dim monocytes and CD16dim neutrophil population was distinguished by gating the 25th percentile of main neutrophil population

MOESM1 of Functional analysis of granulocyte and monocyte subpopulations in neonates

Additional file 1: Table S1. Characteristics of analysed populations for activation and burst measurements in comparison to healthy young adults. Values presented as mean ± S

NMR Reveals a Different Mode of Binding of the Stam2 VHS Domain to Ubiquitin and Diubiquitin,

The VHS domain of the Stam2 protein is a ubiquitin binding domain involved in the recognition of ubiquitinated proteins committed to lysosomal degradation. Among all VHS domains, the VHS domain of Stam proteins is the strongest binder to monoubiqiuitin and exhibits preferences for K63-linked chains. In the present paper, we report the solution NMR structure of the Stam2-VHS domain in complex with monoubiquitin by means of chemical shift perturbations, spin relaxation, and paramagnetic relaxation enhancements. We also characterize the interaction of Stam2-VHS with K48- and K63-linked diubiquitin chains and report the first evidence that VHS binds differently to these two chains. Our data reveal that VHS enters the hydrophobic pocket of K48-linked diubiquitin and binds the two ubiquitin subunits with different affinities. In contrast, VHS interacts with K63-linked diubiquitin in a mode similar to its interaction with monoubiquitin. We also suggest possible structural models for both K48- and K63-linked diubiquitin in interaction with VHS. Our results, which demonstrate a different mode of binding of VHS for K48- and K63-linked diubiquitin, may explain the preference of VHS for K63- over K48-linked diubiquitin chains and monoubiquitin

Abundance dynamics of gut microbiomes of three individuals under treatment with antibiotic Ciprofloxacin (Cp).

(A) NRADs before (green), during (red), and after (blue) treatment. Bold lines are mean NRADs, shaded regions are 90% confidence intervals of the means. (B) MDS of NRADs with one point per NRAD using the same color code as in panel A. For each of the three individuals, arrows connect points corresponding to the last measurement before treatment, measurements during treatment, and the first measurement after treatment. The two coordinates of the MDS plot explain 89% of the NRAD distances.</p

Accuracy of NRAD-based classification.

Accuracy of NRAD-based classification.</p

Optimal parameters for the model of gut microbiome NRAD entropy as function of age.

Optimal parameters for the model of gut microbiome NRAD entropy as function of age.</p

Broken stick distribution (solid line) and NRADs of <i>IgG</i>⁺<i>CD</i>27⁺ fractions (points).

<p>Inset: section of hierarchical clustering dendrogram where broken stick distribution appears. This plot adopts the usual presentation of the broken stick distribution in the literature with linear horizontal axis and logarithmic vertical axis. Therefore the boomerang shapes of the log-log <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005362#pcbi.1005362.g004" target="_blank">Fig 4</a> appear horizontally stretched.</p

Country of origin and age as determinants of gut microbiomes NRADs.

<p>(A) MDS-ordination of NRADs of those 489 gut microbiomes from Malawi/Venezuela (MV) and United States (US) with age information. Small symbols represent individual NRADs, large symbols are averages. Error bars are 90% confidence intervals of the averages. The two coordinates of the MDS plot explain 83% of the NRAD distances. (B) Importance of each of the 4105 NRAD ranks for the random forest classification according to country of origin (MV vs. US). The two peaks around ranks 20 and 200 are the NRAD regions that carry most information about the country of origin.</p

Averaged NRADs of gut microbiome data in six age groups.

<p>The number of NRADs per group from youngest to oldest were 9, 18, 55, 64, 34, and 309, respectively. Solid lines are mean NRADs, shaded areas are 90% confidence intervals for the means.</p