MOESM1 of Defining the fitness of HIV-1 isolates with dual/mixed co-receptor usage

Additional file 1. Characteristics of primary HIV-1 isolates

Comparison of the frequency of variants across NGS platforms.

<p>The heights of the bars represent the combined frequency of V3 variants detected by the NGS platforms 454™, Illumina®, PacBio®, and Ion Torrent™ prior to filtering. The colors within each bar denote the proportional contribution made by each platform after normalization based on coverage. Insets show low frequency variants up to a maximum of 20 unique sequences.</p

Comparison of the clustering of variants across platforms.

<p>The ten most common nucleotide V3 sequences from samples 10–172, 10–176, and 10–180 -obtained with each of the four NGS platforms (454™, Illumina®, PacBio®, and Ion Torrent™)- were aligned against the respective population (sanger) sequence and analyzed as described in the <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049602#pone-0049602-g004" target="_blank">Figure 4</a> legend.</p

Schema summarizing the strategy followed in this study to compare the use of the four next-generation sequencing platforms (454™, Illumina®, PacBio®, and Ion Torrent™) to determine HIV-1 coreceptor tropism (see text for full details).

<p>Schema summarizing the strategy followed in this study to compare the use of the four next-generation sequencing platforms (454™, Illumina®, PacBio®, and Ion Torrent™) to determine HIV-1 coreceptor tropism (see text for full details).</p

Comparison of data processing across NGS platforms.

<p>Number of sequencing errors, substitutions, deletions, and insertions (per read) for the NGS platforms: 454™, Illumina®, PacBio®, and Ion Torrent™. The mean and interquartile range (IQR) are indicated for each sample. Whiskers indicate 1.5 times the IQR as is the default value in the R-statistical package <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049602#pone.0049602-Team1" target="_blank">[75]</a>.</p

HIV-1 coreceptor tropism determination using deep sequencing.

<p>(A) HIV-1 tropism determined at baseline using Trofile™ (Monogram Biosciences) <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049602#pone.0049602-Whitcomb1" target="_blank">[11]</a>; R5, CCR5-tropic virus; D/M, dual mixed. (B) Virologic response at week 12 of a maraviroc-based antiretroviral regimen. Y or N corresponds to plasma viral load below or not 400 copies/ml at week 12, respectively. E.S., end of study (patient did no enter the study following the detection of non-R5 variants at baseline using Trofile™). (C) Quantification of non-R5 variants detected by deep sequencing as predicted using four HIV-1 tropism algorithms, i.e., 11/24/25 rule <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049602#pone.0049602-Archer1" target="_blank">[24]</a>, Geno2Pheno 3.5% FPR <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049602#pone.0049602-Swenson2" target="_blank">[25]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049602#pone.0049602-Swenson3" target="_blank">[28]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049602#pone.0049602-Harrigan1" target="_blank">[42]</a>, Geno2Pheno 10% FPR, and Web PSSM using the subtype B x4r5 matrix <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049602#pone.0049602-Jensen1" target="_blank">[43]</a>. Dotted line represents the ≥2% suggested cutoff for the minimal amount of non-R5 sequences to be present in the viral population in order to classify a given virus as non-R5 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049602#pone.0049602-Swenson2" target="_blank">[25]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049602#pone.0049602-Swenson3" target="_blank">[28]</a>.</p

Environmental health impacts of equine estrogens derived from hormone replacement therapy

Many factors have been considered in evaluations of the risk-benefit balance of hormone replacement therapy (HRT), used for treating menopausal symptoms in women, but not its potential risks for the environment. We investigated the possible environmental health implications of conjugated equine estrogens (CEEs), the most common components of HRT, including their discharge into the environment, their uptake, potency, and ability to induce biological effects in wildlife. Influents and effluents from four UK sewage treatment works (STWs), and bile of effluent-exposed fish, were screened for six equine estrogens. In vitro estrogen receptor (ER) activation assays were applied in humans and fish to compare their potencies, followed by in vivo exposures of fish to equine estrogens and evaluation of bioaccumulation, estrogenic responses, and ER gene expression. The equine estrogen equilenin (Eqn), and its metabolite 17ß-dihydroequilenin (17ß-Eqn), were detected by tandem GC-MSMS in all STW influent samples and 83% of STW effluent samples analyzed, respectively, at low concentrations (0.07-2.6 ng/L) and were taken-up into effluent-exposed fish. As occurs in humans, these estrogens bound to and activated the fish ERs, with potencies at ERa 2.4-3490% of that for 17ß-estradiol. Exposure of fish for 21 days to Eqn and 17ß-Eqn induced estrogenic responses including hepatic growth and vitellogenin production at concentrations as low as 0.6-4.2 ng/L. Associated with these effects were inductions of hepatic ERa and ERß1 gene expression, suggesting ER-mediated mechanism(s) of action. These data provide evidence for the discharge of equine estrogens from HRT into the aquatic environment and highlight a strong likelihood that these compounds contribute to feminization in exposed wildlife