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Biomedical subjects

Simon D W Frost

Publications and source records attributed to Simon D W Frost.

At least 19 recordsLinked to original sources
PubMed2022

Pneumococcal within-host diversity during colonization, transmission and treatment.

Characterizing the genetic diversity of pathogens within the host promises to greatly improve surveillance and reconstruction of transmission chains. For bacteria, it also informs our understanding of inter-strain competition and how this shapes the distribution of resistant and sensitive bacteria. Here we study the genetic diversity of Streptococcus pneumoniae within 468 infants and 145 of their mothers by deep sequencing whole pneumococcal populations from 3,761 longitudinal nasopharyngeal samples. We demonstrate that deep sequencing has unsurpassed sensitivity for detecting multiple colonization, doubling the rate at which highly invasive serotype 1 bacteria were detected in carriage compared with gold-standard methods. The greater resolution identified an elevated rate of transmission from mothers to their children in the first year of the child's life. Comprehensive treatment data demonstrated that infants were at an elevated risk of both the acquisition and persistent colonization of a multidrug-resistant bacterium following antimicrobial treatment. Some alleles were enriched after antimicrobial treatment, suggesting that they aided persistence, but generally purifying selection dominated within-host evolution. Rates of co-colonization imply that in the absence of treatment, susceptible lineages outcompeted resistant lineages within the host. These results demonstrate the many benefits of deep sequencing for the genomic surveillance of bacterial pathogens.

Child↗
PubMed2006

Characteristics of recently HIV-infected men who use the Internet to find male sex partners and sexual practices with those partners.

OBJECTIVE: To examine (1) characteristics of recently HIV-infected men who have sex with men (MSM) who find sex partners through the Internet and (2) differences in characteristics of and sexual behaviors practiced with Internet partners as compared to other partner types. METHODS: From May 2002 to 2005, a computer-assisted self-interview was administered to 194 recently HIV-infected MSM in southern California. MSM who used the Internet to find sex partners were compared with those who did not report Internet use, and partners found from the Internet were compared with those who were found from other venues using chi analyses, t tests, logistic regression, and generalized estimating equations. RESULTS: Seventy percent of participants reported using the Internet to find partners in the prior 3 months. In multivariate analysis, Internet users as compared to non-Internet users reported higher education levels (some college vs. high school: odds ratio [OR] = 5.04; P < 0.01 and college or greater vs. high school: OR = 9.61; P = 0.01), were more likely to be white (OR = 2.16; P = 0.04), reported more partners in the prior 3 months (OR = 1.05; P = 0.04), were more likely to have had sexual contact with all their last 3 partners after HIV diagnosis (OR = 3.43; P < 0.01), and were more likely to report that all their last 3 partners were HIV-negative (OR = 3.35; P = 0.02), but none were main partners (OR = 2.36; P = 0.02). When compared with partners who were found in other venues, Internet partners were less likely to be main partners (OR = 0.52; P < 0.01) and were more likely to be younger (OR = 0.98; P = 0.05), to be HIV-negative (OR = 1.88; P = 0.02), and to become sex partners after HIV diagnosis (OR = 1.58; P = 0.03). CONCLUSIONS: The Internet is a popular venue for recently HIV-infected MSM to find partners, many of whom are HIV-negative. Because finding sex partners through the Internet occurs after HIV diagnosis, the Internet could be a valuable target for new HIV prevention strategies.

Adult↗
PubMed2006

GARD: a genetic algorithm for recombination detection.

MOTIVATION: Phylogenetic and evolutionary inference can be severely misled if recombination is not accounted for, hence screening for it should be an essential component of nearly every comparative study. The evolution of recombinant sequences can not be properly explained by a single phylogenetic tree, but several phylogenies may be used to correctly model the evolution of non-recombinant fragments. RESULTS: We developed a likelihood-based model selection procedure that uses a genetic algorithm to search multiple sequence alignments for evidence of recombination breakpoints and identify putative recombinant sequences. GARD is an extensible and intuitive method that can be run efficiently in parallel. Extensive simulation studies show that the method nearly always outperforms other available tools, both in terms of power and accuracy and that the use of GARD to screen sequences for recombination ensures good statistical properties for methods aimed at detecting positive selection. AVAILABILITY: Freely available http://www.datamonkey.org/GARD/

Algorithms↗
PubMed2006

Evolutionary model selection with a genetic algorithm: a case study using stem RNA.

The choice of a probabilistic model to describe sequence evolution can and should be justified. Underfitting the data through the use of overly simplistic models may miss out on interesting phenomena and lead to incorrect inferences. Overfitting the data with models that are too complex may ascribe biological meaning to statistical artifacts and result in falsely significant findings. We describe a likelihood-based approach for evolutionary model selection. The procedure employs a genetic algorithm (GA) to quickly explore a combinatorially large set of all possible time-reversible Markov models with a fixed number of substitution rates. When applied to stem RNA data subject to well-understood evolutionary forces, the models found by the GA 1) capture the expected overall rate patterns a priori; 2) fit the data better than the best available models based on a priori assumptions, suggesting subtle substitution patterns not previously recognized; 3) cannot be rejected in favor of the general reversible model, implying that the evolution of stem RNA sequences can be explained well with only a few substitution rate parameters; and 4) perform well on simulated data, both in terms of goodness of fit and the ability to estimate evolutionary rates. We also investigate the utility of several distance measures for comparing and contrasting inferred evolutionary models. Using widely available small computer clusters, our approach allows, for the first time, to evaluate the performance of existing RNA evolutionary models by comparing them with a large pool of candidate models and to validate common modeling assumptions. In addition, the new method provides the foundation for rigorous selection and comparison of substitution models for other types of sequence data.

Algorithms↗
PubMed2006

Lack of neutralizing antibody response to HIV-1 predisposes to superinfection.

Occurrences of HIV-1 superinfection offer a unique opportunity to investigate the correlates of immune protection. Here we describe the neutralizing antibody responses of a cohort of recently infected individuals who were screened for HIV superinfection. Three individuals identified with HIV superinfection had less cross-protective and autologous neutralizing antibody response than their non-superinfected case-controls. Neutralizing antibody may be crucial in the protection against superinfection and may explain why superinfection has only been documented following recent infection or treatment interruption. These data have considerable implications for vaccine development.

Adult↗
PubMed2006

Automated phylogenetic detection of recombination using a genetic algorithm.

The evolution of homologous sequences affected by recombination or gene conversion cannot be adequately explained by a single phylogenetic tree. Many tree-based methods for sequence analysis, for example, those used for detecting sites evolving nonneutrally, have been shown to fail if such phylogenetic incongruity is ignored. However, it may be possible to propose several phylogenies that can correctly model the evolution of nonrecombinant fragments. We propose a model-based framework that uses a genetic algorithm to search a multiple-sequence alignment for putative recombination break points, quantifies the level of support for their locations, and identifies sequences or clades involved in putative recombination events. The software implementation can be run quickly and efficiently in a distributed computing environment, and various components of the methods can be chosen for computational expediency or statistical rigor. We evaluate the performance of the new method on simulated alignments and on an array of published benchmark data sets. Finally, we demonstrate that prescreening alignments with our method allows one to analyze recombinant sequences for positive selection.

Algorithms↗
PubMed2006

Adaptation to different human populations by HIV-1 revealed by codon-based analyses.

Several codon-based methods are available for detecting adaptive evolution in protein-coding sequences, but to date none specifically identify sites that are selected differentially in two populations, although such comparisons between populations have been historically useful in identifying the action of natural selection. We have developed two fixed effects maximum likelihood methods: one for identifying codon positions showing selection patterns that persist in a population and another for detecting whether selection is operating differentially on individual codons of a gene sampled from two different populations. Applying these methods to two HIV populations infecting genetically distinct human hosts, we have found that few of the positively selected amino acid sites persist in the population; the other changes are detected only at the tips of the phylogenetic tree and appear deleterious in the long term. Additionally, we have identified seven amino acid sites in protease and reverse transcriptase that are selected differentially in the two samples, demonstrating specific population-level adaptation of HIV to human populations.

Adaptation, Physiological↗
PubMed2006

Respondent-driven sampling of injection drug users in two U.S.-Mexico border cities: recruitment dynamics and impact on estimates of HIV and syphilis prevalence.

Respondent-driven sampling (RDS), a chain referral sampling approach, is increasingly used to recruit participants from hard-to-reach populations, such as injection drug users (IDUs). Using RDS, we recruited IDUs in Tijuana and Ciudad (Cd.) Juárez, two Mexican cities bordering San Diego, CA and El Paso, TX, respectively, and compared recruitment dynamics, reported network size, and estimates of HIV and syphilis prevalence. Between February and April 2005, we used RDS to recruit IDUs in Tijuana (15 seeds, 207 recruits) and Cd. Juárez (9 seeds, 197 recruits), Mexico for a cross-sectional study of behavioral and contextual factors associated with HIV, HCV and syphilis infections. All subjects provided informed consent, an anonymous interview, and a venous blood sample for serologic testing of HIV, HCV, HBV (Cd. Juárez only) and syphilis antibody. Log-linear models were used to analyze the association between the state of the recruiter and that of the recruitee in the referral chains, and population estimates of the presence of syphilis antibody were obtained, correcting for biased sampling using RDS-based estimators. Sampling of the targeted 200 recruits per city was achieved rapidly (2 months in Tijuana, 2 weeks in Cd. Juárez). After excluding seeds and missing data, the sample prevalence of HCV, HIV and syphilis were 96.6, 1.9 and 13.5% respectively in Tijuana, and 95.3, 4.1, and 2.7% respectively in Cd. Juárez (where HBV prevalence was 84.7%). Syphilis cases were clustered in recruitment trees. RDS-corrected estimates of syphilis antibody prevalence ranged from 12.8 to 26.8% in Tijuana and from 2.9 to 15.6% in Ciudad Juárez, depending on how recruitment patterns were modeled, and assumptions about how network size affected an individual's probability of being included in the sample. RDS was an effective method to rapidly recruit IDUs in these cities. Although the frequency of HIV was low, syphilis prevalence was high, particularly in Tijuana. RDS-corrected estimates of syphilis prevalence were sensitive to model assumptions, suggesting that further validation of RDS is necessary.

Adolescent↗
PubMed2005

Neutralizing antibody responses drive the evolution of human immunodeficiency virus type 1 envelope during recent HIV infection.

HIV type 1 (HIV-1) can rapidly escape from neutralizing antibody responses. The genetic basis of this escape in vivo is poorly understood. We compared the pattern of evolution of the HIV-1 env gene between individuals with recent HIV infection whose virus exhibited either a low or a high rate of escape from neutralizing antibody responses. We demonstrate that the rate of viral escape at a phenotypic level is highly variable among individuals, and is strongly correlated with the rate of amino acid substitutions. We show that dramatic escape from neutralizing antibodies can occur in the relative absence of changes in glycosylation or insertions and deletions ("indels") in the envelope; conversely, changes in glycosylation and indels occur even in the absence of neutralizing antibody responses. Comparison of our data with the predictions of a mathematical model support a mechanism in which escape from neutralizing antibodies occurs via many amino acid substitutions, with low cross-neutralization between closely related viral strains. Our results suggest that autologous neutralizing antibody responses may play a pivotal role in the diversification of HIV-1 envelope during the early stages of infection.

Adult↗
PubMed2005

Datamonkey: rapid detection of selective pressure on individual sites of codon alignments.

UNLABELLED: Datamonkey is a web interface to a suite of cutting edge maximum likelihood-based tools for identification of sites subject to positive or negative selection. The methods range from very fast data exploration to the some of the most complex models available in public domain software, and are implemented to run in parallel on a cluster of computers. AVAILABILITY: http://www.datamonkey.org. In the future, we plan to expand the collection of available analytic tools, and provide a package for installation on other systems.

Algorithms↗
PubMed2005

Not so different after all: a comparison of methods for detecting amino acid sites under selection.

We consider three approaches for estimating the rates of nonsynonymous and synonymous changes at each site in a sequence alignment in order to identify sites under positive or negative selection: (1) a suite of fast likelihood-based "counting methods" that employ either a single most likely ancestral reconstruction, weighting across all possible ancestral reconstructions, or sampling from ancestral reconstructions; (2) a random effects likelihood (REL) approach, which models variation in nonsynonymous and synonymous rates across sites according to a predefined distribution, with the selection pressure at an individual site inferred using an empirical Bayes approach; and (3) a fixed effects likelihood (FEL) method that directly estimates nonsynonymous and synonymous substitution rates at each site. All three methods incorporate flexible models of nucleotide substitution bias and variation in both nonsynonymous and synonymous substitution rates across sites, facilitating the comparison between the methods. We demonstrate that the results obtained using these approaches show broad agreement in levels of Type I and Type II error and in estimates of substitution rates. Counting methods are well suited for large alignments, for which there is high power to detect positive and negative selection, but appear to underestimate the substitution rate. A REL approach, which is more computationally intensive than counting methods, has higher power than counting methods to detect selection in data sets of intermediate size but may suffer from higher rates of false positives for small data sets. A FEL approach appears to capture the pattern of rate variation better than counting methods or random effects models, does not suffer from as many false positives as random effects models for data sets comprising few sequences, and can be efficiently parallelized. Our results suggest that previously reported differences between results obtained by counting methods and random effects models arise due to a combination of the conservative nature of counting-based methods, the failure of current random effects models to allow for variation in synonymous substitution rates, and the naive application of random effects models to extremely sparse data sets. We demonstrate our methods on sequence data from the human immunodeficiency virus type 1 env and pol genes and simulated alignments.

Amino Acids↗
PubMed2005

Phenotypic hypersusceptibility to multiple protease inhibitors and low replicative capacity in patients who are chronically infected with human immunodeficiency virus type 1.

Increased susceptibility to the protease inhibitors saquinavir and amprenavir has been observed in human immunodeficiency virus type 1 (HIV-1) with specific mutations in protease (V82T and N88S). Increased susceptibility to ritonavir has also been described in some viruses from antiretroviral agent-naive patients with primary HIV-1 infection in association with combinations of amino acid changes at polymorphic sites in the protease. Many of the viruses displaying increased susceptibility to protease inhibitors also had low replication capacity. In this retrospective study, we analyze the drug susceptibility phenotype and the replication capacity of virus isolates obtained at the peaks of viremia during five consecutive structured treatment interruptions in 12 chronically HIV-1-infected patients. Ten out of 12 patients had at least one sample with protease inhibitor hypersusceptibility (change </=0.4-fold) to one or more protease inhibitor. Hypersusceptibility to different protease inhibitors was observed at variable frequency, ranging from 38% to amprenavir to 11% to nelfinavir. Pairwise comparisons between susceptibilities for the protease inhibitors showed a consistent correlation among all pairs. There was also a significant relationship between susceptibility to protease inhibitors and replication capacity in all patients. Replication capacity remained stable over the course of repetitive cycles of structured treatment interruptions. We could find no association between in vitro replication capacity and in vivo plasma viral load doubling time and CD4(+) and CD8(+) T-cell counts at each treatment interruption. Several mutations were associated with hypersusceptibility to each protease inhibitor in a univariate analysis. This study extends the association between hypersusceptibility to protease inhibitors and low replication capacity to virus isolated from chronically infected patients and highlights the complexity of determining the genetic basis of this phenomenon. The potential clinical relevance of protease inhibitor hypersusceptibility and low replication capacity to virologic response to protease inhibitor-based therapies deserves to be investigated further.

Carbamates↗
PubMed2005

Characterization of human immunodeficiency virus type 1 (HIV-1) envelope variation and neutralizing antibody responses during transmission of HIV-1 subtype B.

We analyzed neutralization sensitivity and genetic variation of transmitted subtype B human immunodeficiency virus type 1 (HIV-1) in eight recently infected men who have sex with men and the virus from the six subjects who infected them. In contrast to reports of heterosexual transmission of subtype C HIV-1, in which the transmitted virus appears to be more neutralization sensitive, we demonstrate that in our study population, relatively few phenotypic changes in neutralization sensitivity or genotypic changes in envelope occurred during transmission of subtype B HIV-1. We suggest that limited genetic variation within the infecting host reduces the likelihood of selective transmission of neutralization-sensitive HIV.

Acute Disease↗
PubMed2004

HyPhy: hypothesis testing using phylogenies.

UNLABELLED: The HyPhypackage is designed to provide a flexible and unified platform for carrying out likelihood-based analyses on multiple alignments of molecular sequence data, with the emphasis on studies of rates and patterns of sequence evolution. AVAILABILITY: http://www.hyphy.org CONTACT: muse@stat.ncsu.edu SUPPLEMENTARY INFORMATION: HyPhydocumentation and tutorials are available at http://www.hyphy.org.

Algorithms↗
PubMed2004

A genetic algorithm approach to detecting lineage-specific variation in selection pressure.

The ratio of nonsynonymous (dN) to synonymous (dS) substitution rates, omega, provides a measure of selection at the protein level. Models have been developed that allow omega to vary among lineages. However, these models require the lineages in which differential selection has acted to be specified a priori. We propose a genetic algorithm approach to assign lineages in a phylogeny to a fixed number of different classes of omega, thus allowing variable selection pressure without a priori specification of particular lineages. This approach can identify models with a better fit than a single-ratio model, and with fits that are better than (in an information theoretic sense) a fully local model, in which all lineages are assumed to evolve under different values of omega, but with far fewer parameters. By averaging over models which explain the data reasonably well, we can assess the robustness of our conclusions to uncertainty in model estimation. Our approach can also be used to compare results from models in which branch classes are specified a priori with a wide range of credible models. We illustrate our methods on primate lysozyme sequences and compare them with previous methods applied to the same data sets.

Algorithms↗
PubMed2004

A simple hierarchical approach to modeling distributions of substitution rates.

Genetic sequence data typically exhibit variability in substitution rates across sites. In practice, there is often too little variation to fit a different rate for each site in the alignment, but the distribution of rates across sites may not be well modeled using simple parametric families. Mixtures of different distributions can capture more complex patterns of rate variation, but are often parameter-rich and difficult to fit. We present a simple hierarchical model in which a baseline rate distribution, such as a gamma distribution, is discretized into several categories, the quantiles of which are estimated using a discretized beta distribution. Although this approach involves adding only two extra parameters to a standard distribution, a wide range of rate distributions can be captured. Using simulated data, we demonstrate that a "beta-" model can reproduce the moments of the rate distribution more accurately than the distribution used to simulate the data, even when the baseline rate distribution is misspecified. Using hepatitis C virus and mammalian mitochondrial sequences, we show that a beta- model can fit as well or better than a model with multiple discrete rate categories, and compares favorably with a model which fits a separate rate category to each site. We also demonstrate this discretization scheme in the context of codon models specifically aimed at identifying individual sites undergoing adaptive or purifying evolution.

Animals↗
PubMed2004

Genetic basis of hypersusceptibility to protease inhibitors and low replicative capacity of human immunodeficiency virus type 1 strains in primary infection.

The initial virus strains from as many as 12% of individuals with primary human immunodeficiency virus (HIV) infection have a 50% inhibitory concentration </=0.4-fold that of HIV type 1(NL4-3) (HIV-1(NL4-3)) to ritonavir (hypersusceptibility [HS]). There is also substantial variation in replicative capacity (RC) or an in vitro assay of the contributions of protease (PR) and reverse transcriptase to viral fitness. In chronically infected antiretrovirally treated patients, amprenavir HS has been associated with the mutation N88S in PR, but this mutation is not seen in untreated patients. In this study, virus strains from 182 cases of primary HIV infection were analyzed, and a highly significant association between HS and low RC (</=10% that of HIV-1(NL4-3)) was observed (P < 10(-6)). Multivariate analysis was used to determine the genotypic basis of ritonavir HS, analyzing all polymorphic amino acid sites and insertions from p7gag through PR. Decision tree models developed on the entire Gag-plus-PR data set and on PR alone gave overall correct classifications of 73 and 72%, respectively, on cross-validation. They were also able to predict low RC, with sensitivities of 69 and 62% and specificities of 84 and 70%, respectively. The analysis shows that ritonavir HS in untreated primary HIV infection is not associated with single mutations but with combinations of amino acids at polymorphic sites and that the same genotypes which confer HS to PR inhibitors confer low RC. This supports the view that variation in PR function is directly responsible for variation in fitness among strains in primary infection.

Decision Trees↗