Overview of crossover study design (adapted from Burton <i>et al</i>., 2017 [21]).

<p>A. Probiotic yoghurt and acidified milk were consumed during two test phases. Postprandial dairy tests (D1 and D2) were completed at the beginning of each test phase and fasting tests were completed after two weeks intake of each product (Fasting 1 and 2). Run-in and wash-out periods respectively preceded and followed the two test phases. Three-day controlled diets were provided prior to all test days and dairy intake was restricted during all study phases. B. Blood sampling on D1 and D2 assessed metabolic, inflammatory and gene expression changes in the six-hour period following dairy intake. All parameters were assessed for the fasting tests. Abbreviations: HOMA, homeostatic model assessment; NEFA, non-esterified fatty acids; hsCRP, high sensitivity C-reactive protein; LPS, lipopolysaccharide; CCL2, chemokine ligand 2; CCL5, chemokine ligand 5; IL6, interleukin 6; TNFα, tumor necrosis factor alpha.</p

Association between expression of the aryl hydrocarbon receptor (<i>AhR</i>) gene in blood cells and circulating concentrations of indole-3-acetaldehyde (IAAld) and insulin.

<p>Postprandial changes in <i>AhR</i> expression (A) and in circulating concentrations of IAAld (B) (Pimentel <i>et al</i>.,<i>submitted</i>) following dairy intake. Postprandial changes of <i>AhR</i> correlate with IAAld after acidified milk intake (rho = -0.43, <i>p</i> = 0.05) but not after yoghurt intake (rho = 0.28, <i>p</i> = 0.20) (C). Changes in <i>AhR</i> expression at 2 h postprandially correlate with changes in insulin at 2 h after yoghurt intake (rho = 0.75, <i>p</i> = 0.05) with a similar trend after acidified milk intake (rho = 0.61, <i>p</i> = 0.14) (D). Acidified milk, blue and yoghurt, red. Symbols represent the time of sampling: 2 h (circles), 4 h (triangles) and 6 h (squares). Abbreviations: <i>AhR</i>, aryl hydrocarbon receptor; IAAld, indole acetaldehyde.</p

Modeling of the viral life cycle.

<p>(<b>A</b>) Raw data of measured viral replication intermediates (mean [dots] with one standard error) and curves of fitted progression model (solid lines). The temporal dynamics of each step in the viral life cycle was generated individually by modeling the net effect of production, decay, initial viral input, and experimental noise of the corresponding marker intermediate (<b><a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1003161#ppat.1003161.s001" target="_blank">Text S1</a></b> and <b>Figure S4</b> and <b>S5 in <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1003161#ppat.1003161.s001" target="_blank">Text S1</a></b>). (<b>B</b>) Activity profile of individual steps of the viral life cycle estimated from the progression model. Each violin spans the 98% quantile of the viral step with width proportional to activity level at each given point in time. The plus symbol (‘+’) denotes the peak of the activity and the inner white violin its 95% bootstrap confidence interval. In the shaded area, expected values extrapolated beyond the last observed time point (24 h, dashed line) are shown.</p

Similarities and differences in the regulation of genes that contribute to enrichments of the inflammatory response geneset after dairy intake.

<p>Each bar shows the total number of genes that contributed to the enrichment for the indicated condition (yoghurt or acidified milk; 2, 4 or 6 h postprandially) and the bar is coloured to indicate whether the genes in the enrichment were regulated in the same manner after the alternative dairy product. Abbreviations: AM, acidified milk; Y, yoghurt.</p

Core gene validation.

<p>RT-qPCR was used to validate key patterns of expression using heat-inactivated virus, primary cells, and natural viral envelope. (<b>A</b>) Analysis of 14 representative genes using competent or heat-inactivated HIV-based vector. The graphs depict the 24 dynamics of expression (log₂ fold change of VSV.G pseudotyped HIV-infected over mock) of eight upregulated genes (red lines), five downregulated genes (blue), and one control (<i>RPL31</i>, black line) in SupT1 cells exposed to similar amount of viral particles, only competent HIV (top panel), 1∶10 competent HIV∶heat-inactivated HIV (middle panel), and only heat-inactivated HIV (bottom panel). (<b>B</b>) Analysis in primary CD4+ T cells isolated from two healthy blood donors. Depicted are the 24 dynamics of expression (log₂ fold change of VSV.G pseudotyped HIV-infected over mock) of the upregulated (red), downregulated (blue), and control (black) genes. (<b>C</b>) Correlation analysis of RT-qPCR for the 14 representative genes at all time points in primary cells (donor 1) infected by VSV.G or CXCR4 pseudotyped HIV. Log₂ fold change linear regression yielded <i>r²</i> = 0.22, <i>p</i><10⁻⁴.</p

Genes that are implicated in the differential regulation of A. KEGG insulin signaling pathway and B. oxidative phosphorylation pathway at 2 h.

<p>The median response for each gene is illustrated by a bar (blue for acidified milk, red for yoghurt) and ordered by the dairy condition that elicited the greatest change in gene expression. Lighter colours show non-significant responses and dark shades show a significant change after intake of the dairy product (<i>p</i> < 0.01).</p

Postprandial changes of genes implicated in the regulation of the inflammatory pathway after intake of yoghurt or acidified milk.

<p>The genes contribute to up-regulation of the pathway at 2 h following both dairy products (acidified milk <i>p</i>_adj = 0.10, yoghurt <i>p</i>_adj = 0.16), and down-regulation of the pathway at 4 h and 6 h (acidified milk 4 h <i>p</i>_adj = 0.14 and 6 h <i>p</i>_adj > 0.20, yoghurt 4 h <i>p</i>_adj = 0.04 and 6 h <i>p</i>_adj = 0.07). The median change in gene expression (with respect to fasting levels) is illustrated for each gene by a single bar (red for yoghurt, blue for acidified milk). Lighter colours show non-significant changes as compared to dark shades (<i>p</i> < 0.01). Genes are ranked by the greatest change at 2 h to observe the evolution of the postprandial response.</p

Clusters of host genes correlated with viral progression.

<p>Temporal expression patterns of 7,991 genes modulated in concordance with key steps of viral replication (panel <b>A</b>) were grouped into 18 clusters with differential expression profiles at three phases of the viral life cycle, namely reverse transcription, integration, and late phase. The cluster code characters ‘+’ and ‘−’ mark significant (<i>p</i><10⁻²) upregulation and downregulation, respectively, while ‘o’ indicates no significant deviation from zero. For example, the cluster ‘−+o’ contains 373 genes downregulated during reverse transcription, upregulated during integration, and unregulated during the late phase. In total, six upregulated clusters (<b>B</b>), four clusters with mixed patterns of regulation (<b>C</b>), and eight downregulated clusters (<b>D</b>) were found. Details of clusters are available at the dedicated web resource <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1003161#ppat.1003161-Bartha1" target="_blank">[6]</a>.</p

Transcriptome changes upon exposure to infectious and non-infectious viral particles.

<p>Principal component analysis is used to explore the overall variance structure of the transcriptome datasets. With each point representing a whole transcriptome sample, the figure presents the transcriptome of cells that were universally infected (HIV), cells exposed to heat-inactivated virus (Heat-inactivated), cells exposed to a mixture of 1∶10 infectious/heat-inactivated virus (HIV[1/10]), and non-infected cells (Mock). One mock sample failed and is not plotted. The transcriptome of mock cells and that of cells exposed to heat-inactivated viruses clustered together across the top principal components. Infected cells, on the other hand, spread away from the mock space as infection progressed, with the most distant dot corresponding to the latest time point (24 h). The mixture 1/10 infectious/noninfectious material occupies the intermediate space. Clustering of the two hours samples corresponds to end of cell exposure to the virus or control materials.</p

Siglec-1 is up-regulated in highly <i>trans</i>-infecting LPS mDCs.

<p>(A) (Left) Comparative HIV-1 capture of LPS and ITIP mDCs: cells were cultured with HIV-1, washed, and lysed to measure viral p24^Gag antigen by ELISA. (Right) Comparative transmission of captured HIV-1 from LPS and ITIP mDCs to a reporter CD4⁺ cell line. Graphs show mean values and standard error of the means (SEMs) from two independent experiments including cells from six donors. (B) Plot of <i>SIGLEC</i> genes (in open circles), <i>CD86</i> and <i>DC-SIGN</i> (in grey circles) computing the fold change in LPS mDCs compared to ITIP mDCs, and the average gene expression across all samples. Circle size is inversely proportional to adjusted <i>p</i> values. Highlighted in red are statistically differentially expressed genes. Analysis was performed with DCs from four donors matured in parallel with the different stimuli. (C) Relative quantification of <i>SIGLEC1</i> mRNA expression levels in distinct DCs analyzed by qRT-PCR. Measurements were normalized using the endogenous control housekeeping gene <i>Beta Glucuronidase</i>. Data show means and SEMs of samples from six donors. (D) Cell surface expression of Siglec-1 in distinct DCs analyzed by FACS with mAb 7–239-PE. (Left graph) Geometric mean fluorescence intensity (MFI) of Siglec-1. (Right graph) Percentage of Siglec-1 positive cells. Data show mean values and SEM from two experiments, including cells from six donors. (Histograms) Representative profiles of Siglec-1 staining in distinct DCs derived from one donor.</p