Estimation of genetic diversity in viral populations from next generation sequencing data with extremely deep coverage

In this paper we propose a method and discuss its computational implementation as an integrated tool for the analysis of viral genetic diversity on data generated by high-throughput sequencing. Most methods for viral diversity estimation proposed so far are intended to take benefit of the longer reads produced by some NGS platforms in order to estimate a population of haplotypes. Our goal here is to take advantage of distinct virtues of a certain kind of NGS platform - the platform SOLiD (Life Technologies) is an example - that has not received much attention due to the short length of its reads, which renders haplotype estimation very difficult. However, this kind of platform has a very low error rate and extremely deep coverage per site and our method is designed to take advantage of these characteristics. We propose to measure the populational genetic diversity through a family of multinomial probability distributions indexed by the sites of the virus genome, each one representing the populational distribution of the diversity per site. The implementation of the method focuses on two main optimization strategies: a read mapping/alignment procedure that aims at the recovery of the maximum possible number of short-reads; the estimation of the multinomial parameters through a Bayesian approach, which, unlike simple frequency counting, allows one to take into account the prior information of the control population within the inference of a posterior experimental condition and provides a natural way to separate signal from noise, since it automatically furnishes Bayesian confidence intervals. The methods described in this paper have been implemented as an integrated tool called Tanden (Tool for Analysis of Diversity in Viral Populations).Comment: 30 pages, 5 figures, 2 tables, Tanden is written in C# (Microsoft), runs on the Windows operating system, and can be downloaded from: http://tanden.url.p

Genetic diversity of Leishmania amazonensis strains isolated in northeastern Brazil as revealed by DNA sequencing, PCR-based analyses and molecular karyotyping

Abstract\ud \ud \ud \ud Background\ud \ud Leishmania (Leishmania) amazonensis infection in man results in a clinical spectrum of disease manifestations ranging from cutaneous to mucosal or visceral involvement. In the present study, we have investigated the genetic variability of 18 L. amazonensis strains isolated in northeastern Brazil from patients with different clinical manifestations of leishmaniasis. Parasite DNA was analyzed by sequencing of the ITS flanking the 5.8 S subunit of the ribosomal RNA genes, by RAPD and SSR-PCR and by PFGE followed by hybridization with gene-specific probes.\ud \ud \ud \ud Results\ud \ud ITS sequencing and PCR-based methods revealed genetic heterogeneity among the L. amazonensis isolates examined and molecular karyotyping also showed variation in the chromosome size of different isolates. Unrooted genetic trees separated strains into different groups.\ud \ud \ud \ud Conclusion\ud \ud These results indicate that L. amazonensis strains isolated from leishmaniasis patients from northeastern Brazil are genetically diverse, however, no correlation between genetic polymorphism and phenotype were found.We thank Lucile FloeterWinter for critical reading of the manuscript and Artur T.L. de Queiroz for initial help with phylogenetic analysis. This work is supported by grants from CNPq, FAPESB and PAPES/FIOCRUZ. J.P.C. de Oliveira was supported by a CNPq fellowship; C.I.O. and F.M.C.F were supported by a FAPESB fellowship. AAC, AB, and CIO are senior investigators from CNPq. AB is a senior investigator for Instituto de Investigação em Imunologia (iii).We thank Lucile Floeter-Winter for critical reading of the manuscript and Artur T.L. de Queiroz for initial help with phylogenetic analysis. This work is supported by grants from CNPq, FAPESB and PAPES/FIOCRUZ. J.P.C. de Oliveira was supported by a CNPq fellowship; C.I.O. and F.M.C.F were supported by a FAPESB fellowship. AAC, AB, and CIO are senior investigators from CNPq. AB is a senior investigator for Instituto de Investigação em Imunologia (iii)

Clinical features and outcomes of elderly hospitalised patients with chronic obstructive pulmonary disease, heart failure or both

Background and objective: Chronic obstructive pulmonary disease (COPD) and heart failure (HF) mutually increase the risk of being present in the same patient, especially if older. Whether or not this coexistence may be associated with a worse prognosis is debated. Therefore, employing data derived from the REPOSI register, we evaluated the clinical features and outcomes in a population of elderly patients admitted to internal medicine wards and having COPD, HF or COPD + HF. Methods: We measured socio-demographic and anthropometric characteristics, severity and prevalence of comorbidities, clinical and laboratory features during hospitalization, mood disorders, functional independence, drug prescriptions and discharge destination. The primary study outcome was the risk of death. Results: We considered 2,343 elderly hospitalized patients (median age 81 years), of whom 1,154 (49%) had COPD, 813 (35%) HF, and 376 (16%) COPD + HF. Patients with COPD + HF had different characteristics than those with COPD or HF, such as a higher prevalence of previous hospitalizations, comorbidities (especially chronic kidney disease), higher respiratory rate at admission and number of prescribed drugs. Patients with COPD + HF (hazard ratio HR 1.74, 95% confidence intervals CI 1.16-2.61) and patients with dementia (HR 1.75, 95% CI 1.06-2.90) had a higher risk of death at one year. The Kaplan-Meier curves showed a higher mortality risk in the group of patients with COPD + HF for all causes (p = 0.010), respiratory causes (p = 0.006), cardiovascular causes (p = 0.046) and respiratory plus cardiovascular causes (p = 0.009). Conclusion: In this real-life cohort of hospitalized elderly patients, the coexistence of COPD and HF significantly worsened prognosis at one year. This finding may help to better define the care needs of this population

HIV-1 Tropism Determines Different Mutation Profiles in Proviral DNA

<div><p>In order to establish new infections HIV-1 particles need to attach to receptors expressed on the cellular surface. HIV-1 particles interact with a cell membrane receptor known as CD4 and subsequently with another cell membrane molecule known as a co-receptor. Two major different co-receptors have been identified: C-C chemokine Receptor type 5 (CCR5) and C-X-C chemokine Receptor type 4 (CXCR4) Previous reports have demonstrated cellular modifications upon HIV-1 binding to its co-receptors including gene expression modulations. Here we investigated the effect of viral binding to either CCR5 or CXCR4 co-receptors on viral diversity after a single round of reverse transcription. CCR5 and CXCR4 pseudotyped viruses were used to infect non-stimulated and stimulated PBMCs and purified CD4 positive cells. We adopted the SOLiD methodology to sequence virtually the entire proviral DNA from all experimental infections. Infections with CCR5 and CXCR4 pseudotyped virus resulted in different patterns of genetic diversification. CCR5 virus infections produced extensive proviral diversity while in CXCR4 infections a more localized substitution process was observed. In addition, we present pioneering results of a recently developed method for the analysis of SOLiD generated sequencing data applicable to the study of viral quasi-species. Our findings demonstrate the feasibility of viral quasi-species evaluation by NGS methodologies. We presented for the first time strong evidence for a host cell driving mechanism acting on the HIV-1 genetic variability under the control of co-receptor stimulation. Additional investigations are needed to further clarify this question, which is relevant to viral diversification process and consequent disease progression.</p></div

Depth coverage of SOLiD sequencing per experimental condition covering positions 790 to 9085 of the HIV-1 pNL4-3 reference genome^*.

<p>*HIV-1 pNL4-3 reference genome [GenBank accession number AF324493]. Presented data correspond to number of reads obtained from each condition.</p><p>Depth coverage of SOLiD sequencing per experimental condition covering positions 790 to 9085 of the HIV-1 pNL4-3 reference genome^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0139037#t003fn001" target="_blank">*</a>}.</p

Influence of envelope tropism, cell type, and stimulation status over proviral nucleotide probabilities after one round of reverse transcription.

<p><b>A)</b> Quantitative and qualitative changes occurring along gag-pol and env regions from X4 versus R5 pseudotyped virus infections. <b>B)</b> Quantitative and qualitative changes occurring along gag-pol and env regions from infected T CD4 + positive cells versus PBMCs. <b>C)</b> Quantitative and qualitative changes occurring along gag-pol and env regions from non-stimulated and stimulated. Asterisks indicate statistical difference at 5% of significance level between compared numbers. Probabilities are presented as percentage (%).</p

Coding regions and mutated codons.

<p>Original codons are the most probable codons observed in control; mutated codons are those determined by nucleotide changes in X4 pseudotyped experiments, bold capital letters indicate base substitutions within affected codons, mutated amino acids are underlined; the 2 last columns indicate codons and amino acids at the same positions in the HIV-1 reference strain (NL4-3 GenBank accession number AF324493).</p><p>Coding regions and mutated codons.</p

Nucleotide changes leading to non synonymous amino acids substitutions in the <i>env</i> coding region and selected known domains in the translated protein.

<p>Numbers indicate nucleotide positions. V2: variable region 2, FP: fusion peptide, HP1 and 2: heptad repeat regions 1 and 2, LLP3 and 1: lentivirus lytic peptide region 3 and 1.</p

Expression of Activation Markers using flow cytometry assays.

<p>Histograms showing the expression of CD25, CD69, CD38 and HLA-DR from gated CD3+CD4+ cell populations from PBMCs are shown in the upper row. Histograms indicating the expression of CD25, CD69 from gated CD3+CD4+ cell populations from purified T CD4+ cells appear in the lower row. X axis indicates the fluoresce intensity of a specific marker and Y axis indicates the percentage of cells in the population expressing this specific marker. Graphics under each histogram represent the MFI (Median of Fluorescence Intensity) of each activation marker in the gated CD3+CD4+ cell populations. Results are shown as mean values ± SD and are representative from three independent experiments. Statistical significance was assessed by the Two-tailed Student’s t-test yielding * when p < 0.05; and **, when p < 0.005. Gray area: unstained control cells, green/blue line: non-stimulated cells, red line: stimulated cells.</p