New insights into the evolutionary rate of HIV-1 at the within-host and epidemiological levels

Over calendar time, HIV-1 evolves considerably faster within individuals than it does at the epidemic level. This is a surprising observation since, from basic population genetic theory, we would expect the genetic substitution rate to be similar across different levels of biological organization. Three different mechanisms could potentially cause the observed mismatch in phylogenetic rates of divergence: temporal changes in selection pressure during the course of infection; frequent reversion of adaptive mutations after transmission; and the storage of the virus in the body followed by the preferential transmission of stored ancestral virus. We evaluate each of these mechanisms to determine whether they are likely to make a major contribution to the mismatch in phylogenetic rates. We conclude that the cycling of the virus through very long-lived memory CD4+ T cells, a process that we call ‘store and retrieve’, is probably the major contributing factor to the rate mismatch. The preferential transmission of ancestral virus needs to be integrated into evolutionary models if we are to accurately predict the evolution of immune escape, drug resistance and virulence in HIV-1 at the population level. Moreover, early infection viruses should be the major target for vaccine design, because these are the viral strains primarily involved in transmission

Modeling microevolution in a changing environment: The evolving quasispecies and the Diluted Champion Process

Several pathogens use evolvability as a survival strategy against acquired immunity of the host. Despite their high variability in time, some of them exhibit quite low variability within the population at any given time, a somehow paradoxical behavior often called the evolving quasispecies. In this paper we introduce a simplified model of an evolving viral population in which the effects of the acquired immunity of the host are represented by the decrease of the fitness of the corresponding viral strains, depending on the frequency of the strain in the viral population. The model exhibits evolving quasispecies behavior in a certain range of its parameters, ans suggests how punctuated evolution can be induced by a simple feedback mechanism.Comment: 15 pages, 12 figures. Figures redrawn, some additional clarifications in the text. To appear in Journal of Statistical Mechanics: Theory and Experimen

Inferring Fitness Effects from Time-Resolved Sequence Data with a Delay-Deterministic Model.

A common challenge arising from the observation of an evolutionary system over time is to infer the magnitude of selection acting upon a specific genetic variant, or variants, within the population. The inference of selection may be confounded by the effects of genetic drift in a system, leading to the development of inference procedures to account for these effects. However, recent work has suggested that deterministic models of evolution may be effective in capturing the effects of selection even under complex models of demography, suggesting the more general application of deterministic approaches to inference. Responding to this literature, we here note a case in which a deterministic model of evolution may give highly misleading inferences, resulting from the nondeterministic properties of mutation in a finite population. We propose an alternative approach that acts to correct for this error, and which we denote the delay-deterministic model. Applying our model to a simple evolutionary system, we demonstrate its performance in quantifying the extent of selection acting within that system. We further consider the application of our model to sequence data from an evolutionary experiment. We outline scenarios in which our model may produce improved results for the inference of selection, noting that such situations can be easily identified via the use of a regular deterministic model

Near-infrared-actuated devices for remotely controlled drug delivery

A reservoir that could be remotely triggered to release a drug would enable the patient or physician to achieve on-demand, reproducible, repeated, and tunable dosing. Such a device would allow precise adjustment of dosage to desired effect, with a consequent minimization of toxicity, and could obviate repeated drug administrations or device implantations, enhancing patient compliance. It should exhibit low off-state leakage to minimize basal effects, and tunable on-state release profiles that could be adjusted from pulsatile to sustained in real time. Despite the clear clinical need for a device that meets these criteria, none has been reported to date to our knowledge. To address this deficiency, we developed an implantable reservoir capped by a nanocomposite membrane whose permeability was modulated by irradiation with a near-infrared laser. Irradiated devices could exhibit sustained on-state drug release for at least 3 h, and could reproducibly deliver short pulses over at least 10 cycles, with an on/off ratio of 30. Devices containing aspart, a fast-acting insulin analog, could achieve glycemic control after s.c. implantation in diabetic rats, with reproducible dosing controlled by the intensity and timing of irradiation over a 2-wk period. These devices can be loaded with a wide range of drug types, and therefore represent a platform technology that might be used to address a wide variety of clinical indications

Variability and genetic diversity among selfed lines (S1) of onion (Allium cepa L.)

Onion is a highly cross-pollinated crop, high variability could possibly come from traditional seed production by out-crossing or by open pollination and it could lead to more diversity and variation. The high phenotypic, genotypic variation coefficients reveal high-quantifiable variation of traits in S1 lines. Selection of lowest premature bolting and split bulbs producing genotypes, least incidence of purple blotch incidence and thrips incidence with the highest weight of ten bulbs and maximum plot yielding genotypes were more appropriate for genetic improvement of onion. The traits aided the yield witnessed high traits heritability (h2) and maximum genetic-advance-mean (GAM) and isolation of S1 lines in terms of selection indices fixed for higher values of measurement. Whereas traits like premature bolting, split bulbs, purple blotch incidence, thrips incidence and were selected at least values although these traits were high heritability (h2) and GAM could contribute for additive-gene-action and hence it indicates the straight mass selection be more effective for genetic improvement of onion genotypes or lines. The genetic distance was highly flanked by Cluster-II and –IV groups and was highly divergent. Hence, the selection of parental lines from these groups is more appropriate for traditional heterosis breeding

Spatial Distribution Patterns for Identifying Risk Areas Associated with False Smut Disease of Rice in Southern India

False smut disease (FSD) of rice incited by Ustilaginoidea virens is an emerging threat to paddy cultivation worldwide. We investigated the spatial distribution of FSD in different paddy ecosystems of South Indian states, viz., Andhra Pradesh, Karnataka, Tamil Nadu, and Telangana, by considering the exploratory data from 111 sampling sites. Point pattern and surface interpolation analyses were carried out to identify the spatial patterns of FSD across the studied areas. The spatial clusters of FSD were confirmed by employing spatial autocorrelation and Ripley’s K function. Further, ordinary kriging (OK), indicator kriging (IK), and inverse distance weighting (IDW) were used to create spatial maps by predicting the values at unvisited locations. The agglomerative hierarchical cluster analysis using the average linkage method identified four main clusters of FSD. From the Local Moran’s I statistic, most of the areas of Andhra Pradesh and Tamil Nadu were clustered together (at I > 0), except the coastal and interior districts of Karnataka (at I < 0). Spatial patterns of FSD severity were determined by semi-variogram experimental models, and the spherical model was the best fit. Results from the interpolation technique, the potential FSD hot spots/risk areas were majorly identified in Tamil Nadu and a few traditional rice-growing ecosystems of Northern Karnataka. This is the first intensive study that attempted to understand the spatial patterns of FSD using geostatistical approaches in India. The findings from this study would help in setting up ecosystem-specific management strategies to reduce the spread of FSD in India

Recombination rate and selection strength in HIV intra-patient evolution

The evolutionary dynamics of HIV during the chronic phase of infection is driven by the host immune response and by selective pressures exerted through drug treatment. To understand and model the evolution of HIV quantitatively, the parameters governing genetic diversification and the strength of selection need to be known. While mutation rates can be measured in single replication cycles, the relevant effective recombination rate depends on the probability of coinfection of a cell with more than one virus and can only be inferred from population data. However, most population genetic estimators for recombination rates assume absence of selection and are hence of limited applicability to HIV, since positive and purifying selection are important in HIV evolution. Here, we estimate the rate of recombination and the distribution of selection coefficients from time-resolved sequence data tracking the evolution of HIV within single patients. By examining temporal changes in the genetic composition of the population, we estimate the effective recombination to be r=1.4e-5 recombinations per site and generation. Furthermore, we provide evidence that selection coefficients of at least 15% of the observed non-synonymous polymorphisms exceed 0.8% per generation. These results provide a basis for a more detailed understanding of the evolution of HIV. A particularly interesting case is evolution in response to drug treatment, where recombination can facilitate the rapid acquisition of multiple resistance mutations. With the methods developed here, more precise and more detailed studies will be possible, as soon as data with higher time resolution and greater sample sizes is available.Comment: to appear in PLoS Computational Biolog

Variability and genetic diversity among selfed lines (S1) of onion (Allium cepa L.)

563-568Onion is a highly cross-pollinated crop, high variability could possibly come from traditional seed production by out-crossing or by open pollination and it could lead to more diversity and variation. The high phenotypic, genotypic variation coefficients reveal high-quantifiable variation of traits in S1 lines. Selection of lowest premature bolting and split bulbs producing genotypes, least incidence of purple blotch incidence and thrips incidence with the highest weight of ten bulbs and maximum plot yielding genotypes were more appropriate for genetic improvement of onion. The traits aided the yield witnessed high traits heritability (h2) and maximum genetic-advance-mean (GAM) and isolation of S1 lines in terms of selection indices fixed for higher values of measurement. Whereas traits like premature bolting, split bulbs, purple blotch incidence, thrips incidence and were selected at least values although these traits were high heritability (h2) and GAM could contribute for additive-gene-action and hence it indicates the straight mass selection be more effective for genetic improvement of onion genotypes or lines. The genetic distance was highly flanked by Cluster-II and –IV groups and was highly divergent. Hence, the selection of parental lines from these groups is more appropriate for traditional heterosis breeding

Accelerated in vivo proliferation of memory phenotype CD4+ T-cells in human HIV-1 infection irrespective of viral chemokine co-receptor tropism.

CD4(+) T-cell loss is the hallmark of HIV-1 infection. CD4 counts fall more rapidly in advanced disease when CCR5-tropic viral strains tend to be replaced by X4-tropic viruses. We hypothesized: (i) that the early dominance of CCR5-tropic viruses results from faster turnover rates of CCR5(+) cells, and (ii) that X4-tropic strains exert greater pathogenicity by preferentially increasing turnover rates within the CXCR4(+) compartment. To test these hypotheses we measured in vivo turnover rates of CD4(+) T-cell subpopulations sorted by chemokine receptor expression, using in vivo deuterium-glucose labeling. Deuterium enrichment was modeled to derive in vivo proliferation (p) and disappearance (d*) rates which were related to viral tropism data. 13 healthy controls and 13 treatment-naive HIV-1-infected subjects (CD4 143-569 cells/ul) participated. CCR5-expression defined a CD4(+) subpopulation of predominantly CD45R0(+) memory cells with accelerated in vivo proliferation (p = 2.50 vs 1.60%/d, CCR5(+) vs CCR5(-); healthy controls; P<0.01). Conversely, CXCR4 expression defined CD4(+) T-cells (predominantly CD45RA(+) naive cells) with low turnover rates. The dominant effect of HIV infection was accelerated turnover of CCR5(+)CD45R0(+)CD4(+) memory T-cells (p = 5.16 vs 2.50%/d, HIV vs controls; P<0.05), naïve cells being relatively unaffected. Similar patterns were observed whether the dominant circulating HIV-1 strain was R5-tropic (n = 9) or X4-tropic (n = 4). Although numbers were small, X4-tropic viruses did not appear to specifically drive turnover of CXCR4-expressing cells (p = 0.54 vs 0.72 vs 0.44%/d in control, R5-tropic, and X4-tropic groups respectively). Our data are most consistent with models in which CD4(+) T-cell loss is primarily driven by non-specific immune activation

Viral population estimation using pyrosequencing

The diversity of virus populations within single infected hosts presents a major difficulty for the natural immune response as well as for vaccine design and antiviral drug therapy. Recently developed pyrophosphate based sequencing technologies (pyrosequencing) can be used for quantifying this diversity by ultra-deep sequencing of virus samples. We present computational methods for the analysis of such sequence data and apply these techniques to pyrosequencing data obtained from HIV populations within patients harboring drug resistant virus strains. Our main result is the estimation of the population structure of the sample from the pyrosequencing reads. This inference is based on a statistical approach to error correction, followed by a combinatorial algorithm for constructing a minimal set of haplotypes that explain the data. Using this set of explaining haplotypes, we apply a statistical model to infer the frequencies of the haplotypes in the population via an EM algorithm. We demonstrate that pyrosequencing reads allow for effective population reconstruction by extensive simulations and by comparison to 165 sequences obtained directly from clonal sequencing of four independent, diverse HIV populations. Thus, pyrosequencing can be used for cost-effective estimation of the structure of virus populations, promising new insights into viral evolutionary dynamics and disease control strategies.Comment: 23 pages, 13 figure