A Generalized Entropy Measure of Within-Host Viral Diversity for Identifying Recent HIV-1 Infections

Evaluation of the HIV-1 Polymerase Gene Sequence Diversity for Prediction of Recent HIV-1 Infections Using Shannon Entropy Analysis

HIV-1 incidence is an important parameter for assessing the impact of HIV-1 interventions. The aim of this study was to evaluate HIV-1 polymerase (pol) gene sequence diversity for the prediction of recent HIV-1 infections. Complete pol Sanger sequences obtained from 45 participants confirmed to have recent or chronic HIV-1 infection were used. Shannon entropy was calculated for amino acid (aa) sequences for the entire pol and for sliding windows consisting of 50 aa each. Entropy scores for the complete HIV-1 pol were significantly higher in chronic compared to recent HIV-1 infections (p < 0.0001) and the same pattern was observed for some sliding windows (p-values ranging from 0.011 to <0.001), leading to the identification of some aa mutations that could discriminate between recent and chronic infection. Different aa mutation groups were assessed for predicting recent infection and their performance ranged from 64.3% to 100% but had a high false recency rate (FRR), which was decreased to 19.4% when another amino acid mutation (M456) was included in the analysis. The pol-based molecular method identified in this study would not be ideal for use on its own due to high FRR; however, this method could be considered for complementing existing serological assays to further reduce FRR.

CEPS: An Open Access MATLAB Graphical User Interface (GUI) for the Analysis of Complexity and Entropy in Physiological Signals

BACKGROUND

We developed CEPS as an open access MATLAB^® GUI (graphical user interface) for the analysis of Complexity and Entropy in Physiological Signals (CEPS), and demonstrate its use with an example data set that shows the effects of paced breathing (PB) on variability of heart, pulse and respiration rates. CEPS is also sufficiently adaptable to be used for other time series physiological data such as EEG (electroencephalography), postural sway or temperature measurements.

METHODS

Data were collected from a convenience sample of nine healthy adults in a pilot for a larger study investigating the effects on vagal tone of breathing paced at various different rates, part of a development programme for a home training stress reduction system.

RESULTS

The current version of CEPS focuses on those complexity and entropy measures that appear most frequently in the literature, together with some recently introduced entropy measures which may have advantages over those that are more established. Ten methods of estimating data complexity are currently included, and some 28 entropy measures. The GUI also includes a section for data pre-processing and standard ancillary methods to enable parameter estimation of embedding dimension m and time delay τ ('tau') where required. The software is freely available under version 3 of the GNU Lesser General Public License (LGPLv3) for non-commercial users. CEPS can be downloaded from Bitbucket. In our illustration on PB, most complexity and entropy measures decreased significantly in response to breathing at 7 breaths per minute, differentiating more clearly than conventional linear, time- and frequency-domain measures between breathing states. In contrast, Higuchi fractal dimension increased during paced breathing.

CONCLUSIONS

We have developed CEPS software as a physiological data visualiser able to integrate state of the art techniques. The interface is designed for clinical research and has a structure designed for integrating new tools. The aim is to strengthen collaboration between clinicians and the biomedical community, as demonstrated here by using CEPS to analyse various physiological responses to paced breathing.

Subclinical Cytomegalovirus and Epstein-Barr Virus Shedding Is Associated with Increasing HIV DNA Molecular Diversity in Peripheral Blood during Suppressive Antiretroviral Therapy

Cytomegalovirus (CMV) almost universally infects persons with HIV (PWH), and it is a driver of persistent inflammation and HIV persistence. The mechanisms underlying the association between CMV (and possibly other herpesviruses) and HIV persistence are unclear. Serially collected blood samples were obtained from men who have sex with men (MSM) who started antiretroviral therapy (ART) within 1 year of their estimated date of HIV infection (EDI). Total CMV and Epstein-Barr virus (EBV) DNA were quantified in peripheral blood mononuclear cells by droplet digital PCR (ddPCR). Deep sequencing of the HIV DNA partial env gene was performed, and the dynamics of viral diversity over time were analyzed in relation to CMV and EBV shedding status. In total, 37 MSM PWH were included and followed for a median of 23 months (IQR, 22 to 28). Participants started ART within a median of 3.1 months (IQR, 1.5 to 6.5) after EDI and remained virally suppressed thereafter. A total of 18 participants (48.6%) were classified as high EBV shedders, while 19 (51.4%) were classified as CMV shedders. In longitudinal analyses, normalized molecular diversity levels tended to increase over time among participants with detectable CMV and high EBV DNA (0.03 ± 0.02, P = 0.08), while they significantly declined among participants with no/low viral shedding (-0.04 ± 0.02, P = 0.047, interaction P < 0.01). Subclinical CMV and EBV shedding could contribute to the dynamics of the HIV DNA reservoir during suppressive ART. Whether persistent CMV/EBV replication could be targeted as a strategy to reduce the size of the latent HIV reservoir is an avenue that should be explored.IMPORTANCE As part of this study, we evaluated the molecular characteristics of the HIV DNA reservoir over time during antiretroviral treatment (ART) in relation to those of other chronic viral infections (i.e., cytomegalovirus [CMV] and Epstein-Barr virus [EBV]). We demonstrated that the presence of CMV and high-level EBV DNA in peripheral blood cells was associated with changes in HIV DNA molecular diversity. Specifically, HIV DNA molecular diversity increased over time among participants with detectable CMV and high-level EBV DNA, while it significantly declined among participants with no/low viral shedding. Although the current study design does not allow causality to be inferred, it does support the theory that persistent CMV and EBV shedding could contribute to the dynamics of the HIV DNA reservoir during suppressive ART, even when ART is initiated during the earliest phases of HIV infection.

HIITE: HIV-1 incidence and infection time estimator

Motivation

Around 2.1 million new HIV-1 infections were reported in 2015, alerting that the HIV-1 epidemic remains a significant global health challenge. Precise incidence assessment strengthens epidemic monitoring efforts and guides strategy optimization for prevention programs. Estimating the onset time of HIV-1 infection can facilitate optimal clinical management and identify key populations largely responsible for epidemic spread and thereby infer HIV-1 transmission chains. Our goal is to develop a genomic assay estimating the incidence and infection time in a single cross-sectional survey setting.

Results

We created a web-based platform, HIV-1 incidence and infection time estimator (HIITE), which processes envelope gene sequences using hierarchical clustering algorithms and informs the stage of infection, along with time since infection for incident cases. HIITE's performance was evaluated using 585 incident and 305 chronic specimens' envelope gene sequences collected from global cohorts including HIV-1 vaccine trial participants. HIITE precisely identified chronically infected individuals as being chronic with an error less than 1% and correctly classified 94% of recently infected individuals as being incident. Using a mixed-effect model, an incident specimen's time since infection was estimated from its single lineage diversity, showing 14% prediction error for time since infection. HIITE is the first algorithm to inform two key metrics from a single time point sequence sample. HIITE has the capacity for assessing not only population-level epidemic spread but also individual-level transmission events from a single survey, advancing HIV prevention and intervention programs.

Availability and implementation

Web-based HIITE and source code of HIITE are available at http://www.hayounlee.org/software.html.

Supplementary information

Supplementary data are available at Bioinformatics online.

Impact of antiretroviral resistance and virological failure on HIV-1 informational entropy

Objectives

The present study investigated the relationship between genomic variability and resistance of HIV-1 sequences in protease (PR) and reverse transcriptase (RT) regions of the pol gene. In addition, we analysed the resistance among 651 individuals presenting antiretroviral virological failure, from 2009 to 2011, in the state of São Paulo, Brazil.

Methods

The genomic variability was quantified by using informational entropy methods and the relationship between resistance and replicative fitness, as inferred by the residual viral load and CD4+ T cell count.

Results

The number of antiretroviral schemes is related to the number of resistance mutations in the HIV-1 PR (α = 0.2511, P = 0.0003, R2 = 0.8672) and the RT (α = 0.7892, P = 0.0001, R2 = 0.9141). Increased informational entropy rate is related to lower levels of HIV-1 viral loads (α = -0.0121, P = 0.0471, R2 = 0.7923), lower levels of CD4+ T cell counts (α = -0.0120, P = 0.0335, R2 = 0.8221) and a higher number of antiretroviral resistance-related mutations.

Conclusions

Less organized HIV genomes as inferred by higher levels of informational entropy relate to less competent host immune systems, lower levels of HIV replication and HIV genetic evolution as a consequence of antiretroviral resistance.

HIV-1 envelope sequence-based diversity measures for identifying recent infections

Identifying recent HIV-1 infections is crucial for monitoring HIV-1 incidence and optimizing public health prevention efforts. To identify recent HIV-1 infections, we evaluated and compared the performance of 4 sequence-based diversity measures including percent diversity, percent complexity, Shannon entropy and number of haplotypes targeting 13 genetic segments within the env gene of HIV-1. A total of 597 diagnostic samples obtained in 2013 and 2015 from recently and chronically HIV-1 infected individuals were selected. From the selected samples, 249 (134 from recent versus 115 from chronic infections) env coding regions, including V1-C5 of gp120 and the gp41 ectodomain of HIV-1, were successfully amplified and sequenced by next generation sequencing (NGS) using the Illumina MiSeq platform. The ability of the four sequence-based diversity measures to correctly identify recent HIV infections was evaluated using the frequency distribution curves, median and interquartile range and area under the curve (AUC) of the receiver operating characteristic (ROC). Comparing the median and interquartile range and evaluating the frequency distribution curves associated with the 4 sequence-based diversity measures, we observed that the percent diversity, number of haplotypes and Shannon entropy demonstrated significant potential to discriminate recent from chronic infections (p<0.0001). Using the AUC of ROC analysis, only the Shannon entropy measure within three HIV-1 env segments could accurately identify recent infections at a satisfactory level. The env segments were gp120 C2_1 (AUC = 0.806), gp120 C2_3 (AUC = 0.805) and gp120 V3 (AUC = 0.812). Our results clearly indicate that the Shannon entropy measure represents a useful tool for predicting HIV-1 infection recency.

The HIV Genomic Incidence Assay Meets False Recency Rate and Mean Duration of Recency Infection Performance Standards

HIV incidence is a primary metric for epidemic surveillance and prevention efficacy assessment. HIV incidence assay performance is evaluated via false recency rate (FRR) and mean duration of recent infection (MDRI). We conducted a meta-analysis of 438 incident and 305 chronic specimens' HIV envelope genes from a diverse global cohort. The genome similarity index (GSI) accurately characterized infection stage across diverse host and viral factors. All except one chronic specimen had GSIs below 0.67, yielding a FRR of 0.33 [0-0.98] %. We modeled the incidence assay biomarker dynamics with a logistic link function assuming individual variabilities in a Beta distribution. The GSI probability density function peaked close to 1 in early infection and 0 around two years post infection, yielding MDRI of 420 [361, 467] days. We tested the assay by newly sequencing 744 envelope genes from 59 specimens of 21 subjects who followed from HIV negative status. Both standardized residuals and Anderson-Darling tests showed that the test dataset was statistically consistent with the model biomarker dynamics. This is the first reported incidence assay meeting the optimal FRR and MDRI performance standards. Signatures of HIV gene diversification can allow precise cross-sectional surveillance with a desirable temporal range of incidence detection.

Characterization of Humoral Immune Responses against Capsid Protein p24 and Transmembrane Glycoprotein gp41 of Human Immunodeficiency Virus Type 1 in China

The objective of this study was to extend our previous research and to further characterize the humoral immune responses against HIV-1 p24, gp41 and the specific peptides carrying the immunodominant epitopes (IDEs) that react with human serum samples from HIV-1-infected individuals in China. We found that the majority (90.45%, 180/199) of the samples did not react with any of the three HIV-1 p24 peptides carrying IDEs, but did react with the recombinant full-length p24, suggesting that these samples tested in China were primarily directed against the conformational epitopes of HIV-1 p24. In contrast, 84.54% (164/194) of the samples reacted with at least one HIV-1 linear gp41 peptide, in particular the gp41-p1 peptide (amino acids 560-616). Both recently and long-term HIV-1-infected individuals displayed similar humoral immune responses against the recombinant gp41. However, samples from long-term HIV-1-infected subjects but not from recently infected subjects, showed a very strong reaction against the gp41-p1 peptide. The different response patterns observed for the two groups against the gp41 and the peptide gp41-p1 were statistically significant (P<0.01, Chi-square test). These results have direct relevance and importance for design of improved HIV-1 p24 detection assays and the gp41- based immunoassay that can be used to reliably distinguish recent and long-term HIV-1 infection.