20 research outputs found
Recommended from our members
Human Immunodeficiency Virus (HIV)-Infected CCR6+ Rectal CD4+ T Cells and HIV Persistence On Antiretroviral Therapy.
BackgroundIdentifying where human immunodeficiency virus (HIV) persists in people living with HIV and receiving antiretroviral therapy is critical to develop cure strategies. We assessed the relationship of HIV persistence to expression of chemokine receptors and their chemokines in blood (n = 48) and in rectal (n = 20) and lymph node (LN; n = 8) tissue collected from people living with HIV who were receiving suppressive antiretroviral therapy.MethodsCell-associated integrated HIV DNA, unspliced HIV RNA, and chemokine messenger RNA were quantified by quantitative polymerase chain reaction. Chemokine receptor expression on CD4+ T cells was determined using flow cytometry.ResultsIntegrated HIV DNA levels in CD4+ T cells, CCR6+CXCR3+ memory CD4+ T-cell frequency, and CCL20 expression (ligand for CCR6) were highest in rectal tissue, where HIV-infected CCR6+ T cells accounted for nearly all infected cells (median, 89.7%). Conversely in LN tissue, CCR6+ T cells were infrequent, and there was a statistically significant association of cell-associated HIV DNA and RNA with CCL19, CCL21, and CXCL13 chemokines.ConclusionsHIV-infected CCR6+ CD4+ T cells accounted for the majority of infected cells in rectal tissue. The different relationships between HIV persistence and T-cell subsets and chemokines in rectal and LN tissue suggest that different tissue-specific strategies may be required to eliminate HIV persistence and that assessment of biomarkers for HIV persistence may not be generalizable between blood and other tissues
Francisella tularensis induces Th1 like MAIT cells conferring protection against systemic and local infection
Mucosal-associated Invariant T (MAIT) cells are recognized for their antibacterial functions. The protective capacity of MAIT cells has been demonstrated in murine models of local infection, including in the lungs. Here we show that during systemic infection of mice with Francisella tularensis live vaccine strain results in evident MAIT cell expansion in the liver, lungs, kidney and spleen and peripheral blood. The responding MAIT cells manifest a polarised Th1-like MAIT-1 phenotype, including transcription factor and cytokine profile, and confer a critical role in controlling bacterial load. Post resolution of the primary infection, the expanded MAIT cells form stable memory-like MAIT-1 cell populations, suggesting a basis for vaccination. Indeed, a systemic vaccination with synthetic antigen 5-(2-oxopropylideneamino)-6-D-ribitylaminouracil in combination with CpG adjuvant similarly boosts MAIT cells, and results in enhanced protection against both systemic and local infections with different bacteria. Our study highlights the potential utility of targeting MAIT cells to combat a range of bacterial pathogens
Adaptation of Droplet Digital PCR-Based HIV Transcription Profiling to Digital PCR and Association of HIV Transcription and Total or Intact HIV DNA.
The Prion Protein N1 and N2 Cleavage Fragments Bind to Phosphatidylserine and Phosphatidic Acid; Relevance to Stress-Protection Responses
<div><p>Internal cleavage of the cellular prion protein generates two well characterised N-terminal fragments, N1 and N2. These fragments have been shown to bind to anionic phospholipids at low pH. We sought to investigate binding with other lipid moieties and queried how such interactions could be relevant to the cellular functions of these fragments. Both N1 and N2 bound phosphatidylserine (PS), as previously reported, and a further interaction with phosphatidic acid (PA) was also identified. The specificity of this interaction required the N-terminus, especially the proline motif within the basic amino acids at the N-terminus, together with the copper-binding region (unrelated to copper saturation). Previously, the fragments have been shown to be protective against cellular stresses. In the current study, serum deprivation was used to induce changes in the cellular lipid environment, including externalisation of plasma membrane PS and increased cellular levels of PA. When copper-saturated, N2 could reverse these changes, but N1 could not, suggesting that direct binding of N2 to cellular lipids may be part of the mechanism by which this peptide signals its protective response.</p></div
Lipid spot blots identify N1 fragment binding to PS and PA.
<p>A. Diagram showing full length PrP and the regions comprising the N1 and N2 cleavage fragments. <b>B.</b> Schematic indicating the lipid spot arrangement on the membrane. <b>C.</b> PrP23-111 (N1) incubation with the lipid spot blots at pH 7 and pH 5 with and without pre-loading with four molar equivalents CuCl<sub>2</sub> followed by western blotting with SAF32 antibody (directed against amino acids 51–89). <b>D.</b> Densitometric quantification of spot intensity, n = 3, significance over blank control is shown as *p<0.05, ***p<0.001.</p
Serum deprivation causes changes to PS and PA in CF10 cells.
<p><b>A.</b> Laurdan GP changes following serum deprivation for 30 minutes as compared with benzyl alcohol (BA) and filipin III controls. n = 3. <b>B.</b> Live cell imaging of NBD-PS labelled CF10 cells. Image intensity is thresholds have been selected to view detail in the staining pattern and do not represent a comparison of fluorescence intensity. Scale bars = 20 μm. <b>C.</b> Fluorescence emission spectra of NBD-PS labelled cells following transfer into serum-free medium, scans were taken immediately after media replacement. <b>D.</b> Anisotropy of NBD-PS in CF10 cells with and without serum present. n = 3. <b>E.</b> Counts from magnetic separation of cells that have lost membrane asymmetry allowing them to bind PS at 5 and 15 minutes post serum withdrawal. n = 4. <b>F.</b> ROS production detected by DCF fluorescence when cells are serum-starved and with exposure to butan-1-ol to inhibit PLD activity. n = 4. <b>G.</b> Measurement of cellular phosphatidic acid concentration 30 minutes after commencing serum deprivation. n = 3. <b>H.</b> Measurement of phospholipase-D activity following 15 minutes serum starvation. n = 3. For all panels, *p<0.05, ***p<0.001.</p
N2 binds PS and PA lipid spots.
<p><b>A.</b> Schematic indicating the lipid spot arrangement on the membrane. <b>B.</b> PrP23-89 (N2) incubation with the lipid spot blots at pH 7 and pH 5 with and without pre-loading with four molar equivalents CuCl<sub>2</sub> followed by western blotting with SAF32 antibody (directed against amino acids 51–89). <b>C.</b> Densitometric quantification of spot intensity, n = 3, significance over blank control and between conditions is shown as *p<0.05, **p<0.01, ***p<0.001.</p
N2, but not N1, reverses PS externalisation and PA increase in the absence of further membrane changes.
<p><b>A.</b> Laurdan GP of serum starved cells alone and when treated N2 (23–89), N1 (23–111), N2 with the two prolines within the N-terminal polybasic region mutated to alanines (23-89P26/28A, the octarepeat region (51–89), copper-saturated (four molar equivalents) N1, N2, 23-89P26/28A and 51–89, 23–50 and equivalent copper without peptide, measured under the same conditions used in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0134680#pone.0134680.g004" target="_blank">Fig 4</a>. n = 3. <b>B.</b> Annexin V magnetic separation of N1 and N2 with and without copper saturation. Filled bar indicates 10% (v/v) serum and hollow bars show conditions with 0% serum. n = 3. <b>C.</b> NBD-PS anisotropy of N2 with and without copper saturation. n = 3. <b>D.</b> Phospholipase-D activity within N1 and N2 (+/- copper), and 23–50 (no copper) serum starved cells. n = 3. <b>E.</b> Relative PA concentrations within N2 treated (+/- copper) serum starved cells. n = 3. Fig *p<0.05.</p
Lipid binding specificity is determined by regions of N1 and N2.
<p>Lipid spot blots (incubated at pH 7) of peptides corresponding to regions of N1 and N2, including residues 23–50 (<b>A</b>), residues 51–89 comprising the copper-binding region and therefore tested with and without copper saturation (<b>B</b>) and an N1 fragment lacking the residues of the copper-binding region, Δ51–89 (<b>C</b>). For 23–50 and N1Δ51–89, copper saturation was not tested as neither fragment contains the octarepeat copper-binding domain and blotting used the N-terminally targeted 8B4 antibody as SAF32 targets residues 79–92. <b>D.</b> Lipid spot blots of a mutant N2 P26/28A fragment with and without copper saturation at pH 7 detected with SAF32. <b>E.</b> Densitometric quantification of spot intensity for the domains of N1 and N2, n = 1. <b>F.</b> Densitometric quantification of spot intensity of the P26/28A mutation of N2 with and without copper saturation. Apo N2 intensities are shown for comparison of differences between the mutated and wild-type (WT) sequence, n = 3. Significance over blank control is shown in black and significant differences in detection from the wild type sequence of N2 are shown in red, *p<0.05, ***p<0.001.</p
Recommended from our members
Adaptation of Droplet Digital PCR-Based HIV Transcription Profiling to Digital PCR and Association of HIV Transcription and Total or Intact HIV DNA.
In most people living with HIV (PLWH) on effective antiretroviral therapy (ART), cell-associated viral transcripts are readily detectable in CD4+ T cells despite the absence of viremia. Quantification of HIV RNA species provides insights into the transcriptional activity of proviruses that persist in cells and tissues throughout the body during ART (HIV reservoir). One such technique for HIV RNA quantitation, HIV transcription profiling, developed in the Yukl laboratory, measures a series of HIV RNA species using droplet digital PCR. To take advantage of advances in digital (d)PCR, we adapted the HIV transcription profiling technique to Qiagens dPCR platform (QIAcuity) and compared its performance to droplet digital (dd)PCR (Bio-Rad QX200 system). Using RNA standards, the two technologies were tested in parallel and assessed for multiple parameters including sensitivity, specificity, linearity, and intra- and inter-assay variability. The newly validated dPCR assays were then applied to samples from PLWH to determine HIV transcriptional activity relative to HIV reservoir size. We report that HIV transcriptional profiling was readily adapted to dPCR and assays performed similarly to ddPCR, with no differences in assay characteristics. We applied these assays in a cohort of 23 PLWH and found that HIV reservoir size, based on genetically intact proviral DNA, does not predict HIV transcriptional activity. In contrast, levels of total DNA correlated with levels of most HIV transcripts (initiated, proximally and distally elongated, unspliced, and completed, but not multiply spliced), suggesting that a considerable proportion of HIV transcripts likely originate from defective proviruses. These findings may have implications for measuring and assessing curative strategies and clinical trial outcomes