The mucosal damage associated to HIV-1 infection leads to translocation of microbial products from the intestinal lumen into the bloodstream.1–5 Levels of microbial translocation (MT) in plasma of HIV-1–infected patients have been frequently determined by the quantification of the plasma levels of lipopolysaccharide (LPS), soluble CD14 (sCD14), lipopolysaccharide binding protein (LBP), or bacterial 16S ribosomal DNA (16S rDNA).
Increased MT has been proposed as one of the main trigger mechanisms for persistent immune activation in HIV-1–infected patients,6–9 a strong predictor for disease progression.10–14 Several studies have reported the association between MT and immune activation in the first years of chronic HIV-1 infection or in the most advanced stages of HIV/AIDS.15–17 However, the dynamics of MT and immune activation in patients with high CD4+ T-cell counts and undetectable plasma viral load are still poorly defined.
The aim of our work was to determine correlations between different techniques employed to measure MT in plasma of HIV-1–infected individuals under suppressive antiretroviral therapy (ART). For this purpose, we analyzed levels of bacterial products as LPS and 16S rDNA and sCD14 marker of monocyte activation and plasma LBP. As a secondary objective, we evaluated the correlation between MT and CD4+ and CD8+ T-cell activation.
MATERIALS AND METHODS
This study was performed within 2 pilot open-label phase II intensification clinical trials conducted at the Hospital Ramón y Cajal in Madrid, Spain, from 2008 to 2012.18,19 The 18 patients included in this study had a median age of 46 (41–50) years and most were male (88%), with a median time on ART of more than 8 years (Table 1). The median CD4 count was 675 cells per cubic millimeter, and all of them had CD4+ T-cell count above 350 cells per cubic millimeter and prolonged viral suppressive ART (<40 HIV-1 RNA copies/mL). Nine patients incorporated a CCR5 antagonist (maraviroc, provided by Pfizer, Inc., New York) to their current suppressive regimen, whereas the other 9 patients intensified their ART with an integrase inhibitor (raltegravir, provided by Merck Sharp and Dhome, Whitehouse Station, NJ).
The 7 time points included in this study were as follows: baseline, before the inclusion of intensifying drugs; weeks 12, 24, 36, and 48 after the inclusion of the intensifying drugs; and weeks 12 and 24 after discontinuation of intensifying drugs. All these 126 samples from the 18 patients at the different time points were analyzed altogether.
MT was measured in plasma by 3 commercial kit assays according to the manufacturer’s protocol. Plasma bacterial LPS was measured using QCL-1000 Limulus Amebocyte Lysate (Lonza, Basel, Switzerland), plasma sCD14 was quantified using the Quantikine Human sCD14 Immunoassay (R&D Systems, Minneapolis, MN) and plasma LBP was measured by LBP soluble ELISA kit (Enzo Life Sciences, Farmingdale, NY). All the samples were run in duplicate.
To perform the bacterial 16S rDNA quantification, DNA was extracted from 200 µL of plasma using QIAamp DNA kit (Qiagen, Hilden, Germany). A standard curve was generated using 10 to106 copies of a recombinant plasmid containing 16S gene fragment (171 bp) for quantification purpose. The amplification reaction was carried out in duplicate using LightCycler 2.0 (Roche Diagnostics, Manheim, Germany) in a total volume of 20 μL containing LightCycler FastStart DNA Master PLUS HybProbe 5X (Roche Diagnostics), 200 ng of DNA, 50 pmol of each primer, 16S-F (5′-AGGTCGCTTCTCTTTGTATGC) and 16S-R (5′-ATGCGCCATTGTAGCACGTGTGT), along with 2 pmol of the following fluorescent probe: 5′-[6FAM]-AAGTCCCGCAACGAGCGCAACCCT-[BQH1]. The cycling parameters included a hot start at 95°C for 10 minutes and continued with 40 cycles of denaturation at 95ºC for 5 seconds, annealing at 55ºC for 10 seconds and extension at 72ºC for 15 seconds.
Fresh ethylenediamine tetraacetic acid anticoagulated whole blood was used to analyze CD4+ and CD8+ T-cell activation with the following antibody combination: CD3-allophycocyanin-Cy7, CD4-peridinin chlorophyll protein complex, CD8-phycoerythrin-Cy7, CD38-phycoerythrin, and HLA-DR-allophycocyanin. Antibodies were from BD (Becton Dickinson, Franklin Lanes, NJ), and an unstained control was performed for all samples. Briefly, 100 µL of blood were lysed with 200 µL of FACS Lysing Solution (Becton Dickinson) for 30 minutes at room temperature, incubated with the antibodies during 20 minutes at 4°C, washed, and resuspended in phosphate-buffered saline containing 1% of azida. Cells were analyzed using a Gallios flow cytometer (Beckman-Coulter, Brea, CA). At least 40,000 CD3+ cells were collected for each sample and analyzed with Kaluza software (Beckman-Coulter) initially gating lymphocytes according to morphological parameters. The gating was always the same between different time points.
LPS and sCD14 levels and immunological parameters were assessed every 12 weeks during the 48 weeks of treatment intensification and also at weeks 12 and 24 after maraviroc and raltegravir removal. However, 16S rDNA levels were determined during the period of treatment intensification (baseline, 12, 24, 36, and 48 weeks during intensification), and LBP levels were assessed at baseline, at week 48 of treatment intensification, and at weeks 12 and 24 after discontinuation of intensifying treatment.
Continuous variables were expressed as the median and interquartile range and discrete variables as percentages. The t test for independent samples was used to compare normally distributed continuous variables and the Mann–Whitney test to compare nonnormally distributed continuous variables. Categorical variables were described as proportions. The association between categorical variables was evaluated using the χ2 test. The Spearman correlation test was used. Statistical analysis was performed using SPSS software 21.0 (SPSS, Inc, Chicago, IL).
Good Correlation Between MT Measurements Except for 16S rDNA
We analyzed the associations among MT measurements performed on 126 determinations from 18 patients, altogether. Plasma LPS determinations positively correlated with levels of sCD14 and LBP (P < 0.001 and P = 0.042, respectively) (Figs. 1A, B). Similarly, high levels of sCD14 were associated with high levels of LBP (P = 0.009) (Fig. 1C). No correlation was found, however, between bacterial 16S rDNA either with LPS, sCD14, or LBP levels (Figs. 1D–F; P = 0.346, P = 0.405, and P = 0.644, respectively).
16S rDNA Level Correlated With Activated CD4+ T Cells, While No Correlation With CD8+ T-Cell Activation Was Evident
We also analyzed the associations between MT and CD4+ and CD8+ T-cell activation, CD4+ and CD8+ T-cell count, and the CD4+/CD8+ ratio. No significant correlation was found between plasma levels of LPS, sCD14, or LBP and activated CD4+ T cells (P = 0.418, P = 0.619, and P = 0.728, respectively) (Fig. 2A) or activated CD8+ T cells (P = 0.352, P = 0.275, and P = 0.124, respectively) (Fig. 2B). However, high levels of bacterial 16S rDNA correlated significantly with high levels of activated CD4+ T cells (P = 0.005) (Fig. 2A) but not with activated CD8+ T cells (P = 0.171) (Fig. 2B).
No association between MT measurements and CD4+ or CD8+ T-cell count or CD4+/CD8+ ratio was observed (data not shown). Similarly, T-cell immune activation showed no significant correlation either with CD4+ or CD8+ T-cell count or CD4+/CD8+ ratio.
In HIV-1–infected patients, elevated LPS in circulation binds the CD14 toll-like receptor 4 (TLR 4) through plasma LBP and triggers the activation of monocytes and macrophages that increase secretion of sCD14 and proinflammatory cytokines.20 Several studies have reported the correlation between LPS and sCD14 levels in HIV-1 immune depressed patients6,20,21 and in patients with undetectable HIV-1 viral load.22 Besides, a correlation between LPS and both LBP and sCD14 levels was found and was associated to HIV-associated dementia in AIDS patients.23
We have observed a significant correlation between plasma LPS, LBP, and sCD14 levels in patients with optimal CD4+ T-cell response (>350 cells/mm3) during prolonged viral suppressive ART (<40 HIV-1 RNA copies/mL), in agreement with previous studies.24 Nevertheless, no correlation between 16S rDNA and the other measurements of MT was found in our study, although this correlation has been reported by other authors who evaluated both treatment-naive and -experienced patients.25,26 The fact that our study included only patients on long-term ART who were virologically suppressed and with good immunological recovery may explain the discrepancy between our results and those of the other studies, including mixed populations.
According to our data, and in this particular group of patients, these 3 markers (sCD14, LPS, and LBP) are suitable to measure MT. Nevertheless, each marker has limitations: sCD14 can be induced by different factors other than LPS in unsuppressed HIV-1 infection27; LPS is only present in Gram-negative bacteria and there are inherent technical difficulties in its measuring, that is, plasmas have to be stored in apyrogenic tubes and handled with care to prevent contamination. On the other hand, although 16S rDNA is present in both Gram-negative and Gram-positive bacteria, it has been technically hampered due to DNA contamination.
MT has been proposed as a possible driver mechanism of immune activation in HIV-1 infection,28–30 supported by the correlation between LPS levels and circulating CD8+ T cells expressing CD38+ and HLA-DR+ observed in chronically infected HIV-1 patients, elite controllers, and naive patients.31 Another group has found a correlation between 16S rDNA and CD8+ T-cell activation (P = 0.047), but only when aviremic- and viremic-treated patients were analyzed together.25 On the other hand, other studies failed to show this correlation during treatment interruption32 or in patients undergoing raltegravir treatment intensification.33 After the scenario of treatment intensification, no correlation between the levels of LPS, LBP, or sCD14 with immune activation was found. Surprisingly, a significant correlation between levels of 16S rDNA and CD4+ T-cell activation was found. We do not have a good explanation for this finding, but the type of patients and the fact that they had been in a treatment intensification scenario could account for this correlation.
Considering these data, we are unable to ensure that MT directly triggers T-cell immune activation, at least among these patients with relatively good immune recovery and under treatment intensification, although this process is clearly an important component of innate immune inflammation associated to HIV-1 infection.
We cannot discard that treatment intensification might affect MT and subsequent correlation with immune activation in different ways depending on the intensifying drug. To discard this possibility, we analyzed individuals who intensified with maraviroc separately from individuals who intensified with raltegravir, obtaining similar results. The discrepancies found in our study compared with others may be attributable to the good immunological characteristics of our cohort undergoing treatment intensification after at least 2 years of antiretroviral treatment maintaining HIV-1 viremia undetectable and high levels of CD4+ T cells (>350 cells/mm3).
In conclusion, the quantification of LPS, LBP, and sCD14 are good measurements of MT and can be used interchangeably, taking into account the technical difficulties in performing each measurement. On the other hand and studying this particular type of patients, long-term suppressed individuals, a poor association between MT and immune activation, was found because only a single correlation between activated CD4+ T cell and 16S rDNA was found. Further studies focusing on the restoration of the gut mucosa in HIV-1 infection would help to clarify the role of MT in HIV-1–associated immune activation and the subsequent immune recovery.
The authors thank C. Page, R. Lorente, E. Domínguez, and M. Coronel for the excellent technical assistance. We are deeply grateful to the patients and their families who participated in this study.
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