<i>FCGR2C</i> polymorphisms associate with FcγR gene expression in B cells in the European (EUR) population.

<p>A. The boxplot shows the distribution of the expression (y-axis) of the last exon (hg19, chr1: 161487765–161489358) of <i>FCGR2A</i> in B cells from the 373 EUR individuals as quantified in [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0152425#pone.0152425.ref007" target="_blank">7</a>], stratified by the genotypes (x-axis) of the SNP rs114945036. Individual expression levels are (horizontal line = median; bottom and top of box = 25^th and 75^th percentile). Expression in individuals is shown in blue dots. The significance of the association is indicated immediately above, which were mapped in [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0152425#pone.0152425.ref007" target="_blank">7</a>] using a linear model implemented in Matrix eQTL [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0152425#pone.0152425.ref010" target="_blank">10</a>]. B. Similar as A, for the SNP rs78603008. C. Similar as A, for the SNP rs138747765. D. Similar as A, for the SNP rs138747765 and the expression of the third exon (hg19, chr1:161680550–161680702) of <i>FCRLA</i> (Fc receptor-like A) in B cells.</p

<i>FCGR2C</i> Polymorphisms Associated with HIV-1 Vaccine Protection Are Linked to Altered Gene Expression of Fc-γ Receptors in Human B Cells

<div><p>The phase III Thai RV144 vaccine trial showed an estimated vaccine efficacy (VE) to prevent HIV-1 infection of 31.2%, which has motivated the search for immune correlates of vaccine protection. In a recent report, several single nucleotide polymorphisms (SNPs) in <i>FCGR2C</i> were identified to associate with the level of VE in the RV144 trial. To investigate the functional significance of these SNPs, we utilized a large scale B cell RNA sequencing database of 462 individuals from the 1000 Genomes Project to examine associations between <i>FCGR2C</i> SNPs and gene expression. We found that the <i>FCGR2C</i> SNPs that associated with vaccine efficacy in RV144 also strongly associated with the expression of <i>FCGR2A/C</i> and one of them also associated with the expression of Fc receptor-like A (<i>FCRLA</i>), another Fc-γ receptor (FcγR) gene that was not examined in the previous report. These results suggest that the expression of FcγR genes is influenced by these SNPs either directly or in linkage with other causal variants. More importantly, these results motivate further investigations into the potential for a causal association of expression and alternative splicing of <i>FCGR2C</i> and other FcγR genes with the HIV-1 vaccine protection in the RV144 trial and other similar studies.</p></div

<i>FCRLA</i> polymorphisms associate with <i>FCRLA</i> expression in human B cells.

<p>A. Scatterplot of the eQTL p-values (-log10 scale) for the association of SNPs across the FcγR region with the expression of <i>FCRLA</i> as mapped in [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0152425#pone.0152425.ref007" target="_blank">7</a>]. For simplicity, for each SNP only the smallest p-value from different levels of expression, i.e. exon, transcript, and gene, is shown. The green vertical bar indicates the location of the <i>FCGR2C</i> SNPs identified in [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0152425#pone.0152425.ref002" target="_blank">2</a>]. The black horizontal line segments at the top indicate the positions of Refseq annotated FcγR genes, with the locations of <i>FCGR2C</i> and <i>FCRLA</i> labeled. B. Close view of SNPs around <i>FCRLA</i> in UCSC genome browser (hg19, chr1:161,670,571–161,688,007). The top track shows the genomic locations and the association p-values (-log10 scale) for those SNPs that passed the significance cutoff of FDR < 0.05 in their associations with the expression of <i>FCRLA</i> at different levels as reported in [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0152425#pone.0152425.ref007" target="_blank">7</a>], i.e. exon, transcript, and gene. Highlighted in color cyan are SNPs with smallest p-values (also see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0152425#pone.0152425.s004" target="_blank">S1 Table</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0152425#pone.0152425.s005" target="_blank">S2 Table</a>). The middle two horizontal tracks show the LD between each of the corresponding SNPs shown on top track and the SNP rs114945036. RefSeq gene annotation is shown at the bottom. C. Scatterplot of raw RNA-seq read counts (log2 scale) of RefSeq annotated <i>FCGR2C</i> (x-axis) and <i>FCRLA</i> (y-axis) in B cells from each of those 462 individuals. The number on the top-right corner shows the Pearson correlation coefficient.</p

SIV vRNA+ Cells in the Lungs of Macaques Infected with SIV¹.

<p>¹Totally 38 infected and 6 uninfected rhesus macaques were used in this study, and vRNA+ cells were quantified by ISH.</p><p>²DPI = Days post infection.</p><p>³Virus load in plasma was detected by real-time RT-PCR.</p><p>⁴SIV vRNA⁺ cells in lungs were detected using ISH with SIV-specific riboprobes:</p><p>−ith SIV-s⁺ cells/mm²</p><p>+, 5–50 vRNA⁺ cells/mm²</p><p>++, 51–100 vRNA⁺ cells/mm²</p><p>++++, >200 vRNA⁺ cells/mm².</p><p>SIV vRNA+ Cells in the Lungs of Macaques Infected with SIV<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125500#t001fn001" target="_blank">¹</a>.</p

The depletion of CD4+ T cells, but not macrophages, in lung tissues during SIV infection.

<p>CD4+ T cells (A-F) and CD68+ macrophages (G-I) in the lung tissues of uninfected and infected macaques detected using immunohistochemical staining and quantified using Aperio Spectrum Plus analysis program. The A-E are representative images of CD4+ T cells in uninfected lung tissues (A-C) and, infected at 10 days (D) and 12 weeks (E) PI respectively. (A) Digitized whole tissue section. (B) Magnified image from the box in the <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125500#pone.0125500.g003" target="_blank">Fig 3A</a>, where the brown corresponds to the stained CD4+ T cells. (C) The red/yellow marked-up regions correspond to the stained CD4+ T cells in the <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125500#pone.0125500.g003" target="_blank">Fig 3B</a> used for quantification with Aperio Spectrum Plus analysis program. The G-H are the representative images of pulmonary CD68+ macrophages in uninfected lung tissues (G) and infected at 12 weeks PI(H). The <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125500#pone.0125500.g003" target="_blank">Fig 3F and 3I</a> are the histograms of CD4+ T cell and macrophage quantification in lung tissues, respectively. X-axis shows the time of infection at 0 (n = 6), 3 (n = 6), 6 (n = 6), 10 (n = 4) days and 12 weeks (n = 4) PI, and y-axis shows the cell number expressed as per square millimeter of lung tissue. *Indicates significant differences from controls (*P<0.05, **P<0.01). Statistical analysis of cell amount per mm² tissue was performed with non-parametric Mann-Whitney U test.</p

SIV vRNA+ cells increase in the lungs of chronically infected macaques as compared with early infection.

<p>SIV vRNA+ cells were detected using <i>in situ</i> hybridization, and appeared as black dots in transmitted light and green dots under epipolarized light. There were a few vRNA+ cells in the lung tissues during acute infection (A1, A2) and large numbers of vRNA+ cells in the lung during chronic infection (B1-D2).</p

Macrophages are the main SIV RNA+ cells in the lungs from very early (A) at 10 days PI to chronic infection at 5 months PI (B).

<p>SIV vRNA+ macrophages were distinguished from T cells by immunohistochemical staining for CD163. The red arrows indicate CD163+ vRNA+ cells identified by the overlying collection of silver grains (black dots); blue arrows indicate SIV RNA+ cells that are not macrophages in lung associated lymphatic tissue (C).</p

Sequencing, Annotation and Analysis of the Syrian Hamster (<i>Mesocricetus auratus</i>) Transcriptome

<div><p>Background</p><p>The Syrian hamster (golden hamster, <i>Mesocricetus auratus</i>) is gaining importance as a new experimental animal model for multiple pathogens, including emerging zoonotic diseases such as Ebola. Nevertheless there are currently no publicly available transcriptome reference sequences or genome for this species.</p><p>Results</p><p>A cDNA library derived from mRNA and snRNA isolated and pooled from the brains, lungs, spleens, kidneys, livers, and hearts of three adult female Syrian hamsters was sequenced. Sequence reads were assembled into 62,482 contigs and 111,796 reads remained unassembled (singletons). This combined contig/singleton dataset, designated as the Syrian hamster transcriptome, represents a total of 60,117,204 nucleotides. Our <i>Mesocricetus auratus</i> Syrian hamster transcriptome mapped to 11,648 mouse transcripts representing 9,562 distinct genes, and mapped to a similar number of transcripts and genes in the rat. We identified 214 quasi-complete transcripts based on mouse annotations. Canonical pathways involved in a broad spectrum of fundamental biological processes were significantly represented in the library. The Syrian hamster transcriptome was aligned to the current release of the Chinese hamster ovary (CHO) cell transcriptome and genome to improve the genomic annotation of this species. Finally, our Syrian hamster transcriptome was aligned against 14 other rodents, primate and laurasiatheria species to gain insights about the genetic relatedness and placement of this species.</p><p>Conclusions</p><p>This Syrian hamster transcriptome dataset significantly improves our knowledge of the Syrian hamster's transcriptome, especially towards its future use in infectious disease research. Moreover, this library is an important resource for the wider scientific community to help improve genome annotation of the Syrian hamster and other closely related species. Furthermore, these data provide the basis for development of expression microarrays that can be used in functional genomics studies.</p></div

Overview of the influenza datasets analysis.

<p>The baseline samples are less than validation samples because of missing baselines measures. For validation and test columns, the number of asymptomatic (asy) subjects and the number of symptomatic (sym) are also shown. And each subject has samples collected at set intervals after inoculation.</p

Ebola virus glycoprotein directly triggers T lymphocyte death despite of the lack of infection

<div><p>Fatal outcomes of Ebola virus (EBOV) infections are typically preceded by a ‘sepsis-like’ syndrome and lymphopenia despite T cells being resistant to Ebola infection. The mechanisms that lead to T lymphocytes death remain largely unknown; however, the degree of lymphopenia is highly correlative with fatalities. Here we investigated whether the addition of EBOV or its envelope glycoprotein (GP) to isolated primary human CD4⁺ T cells induced cell death. We observed a significant decrease in cell viability in a GP-dependent manner, which is suggestive of a direct role of GP in T cell death. Using immunoprecipitation assays and flow cytometry, we demonstrate that EBOV directly binds to CD4⁺ T cells through interaction of GP with TLR4. Transcriptome analysis revealed that the addition of EBOV to CD4⁺ T cells results in the significant upregulation of pathways associated with interferon signaling, pattern recognition receptors and intracellular activation of NFκB signaling pathway. Both transcriptome analysis and specific inhibitors allowed identification of apoptosis and necrosis as mechanisms associated with the observed T cell death following exposure to EBOV. The addition of the TLR4 inhibitor CLI-095 significantly reduced CD4⁺ T cell death induced by GP. EBOV stimulation of primary CD4⁺ T cells resulted in a significant increase in secreted TNFα; inhibition of TNFα-mediated signaling events significantly reduced T cell death while inhibitors of both necrosis and apoptosis similarly reduced EBOV-induced T cell death. Lastly, we show that stimulation with EBOV or GP augments monocyte maturation as determined by an overall increase in expression levels of markers of differentiation. Subsequently, the increased rates of cellular differentiation resulted in higher rates of infection further contributing to T cell death. These results demonstrate that GP directly subverts the host’s immune response by increasing the susceptibility of monocytes to EBOV infection and triggering lymphopenia through direct and indirect mechanisms.</p></div