Mark M. Tanaka

Sequential Monte Carlo without likelihoods.

Recent new methods in Bayesian simulation have provided ways of evaluating posterior distributions in the presence of analytically or computationally intractable likelihood functions. Despite representing a substantial methodological advance, existing methods based on rejection sampling or Markov chain Monte Carlo can be highly inefficient and accordingly require far more iterations than may be practical to implement. Here we propose a sequential Monte Carlo sampler that convincingly overcomes these inefficiencies. We demonstrate its implementation through an epidemiological study of the transmission rate of tuberculosis.

Norovirus Recombination in ORF1/ORF2 Overlap

Norovirus (NoV) genogroups I and II (GI and GII) are now recognized as the predominant worldwide cause of outbreaks of acute gastroenteritis in humans. Three recombinant NoV GII isolates were identified and characterized, 2 of which are unrelated to any previously published recombinant NoV. Using data from the current study, published sequences, database searches, and molecular techniques, we identified 23 recombinant NoV GII and 1 recombinant NoV GI isolates. Analysis of the genetic relationships among the recombinant NoV GII isolates identified 9 independent recombinant sequences; the other 14 strains were close relatives. Two of the 9 independent recombinant NoV were closely related to other recombinants only in the polymerase region, and in a similar fashion 1 recombinant NoV was closely related to another only in the capsid region. Breakpoint analysis of recombinant NoV showed that recombination occurred in the open reading frame (ORF)1/ORF2 overlap. We provide evidence to support the theory of the role of subgenomic RNA promoters as recombination hotspots and describe a simple mechanism of how recombination might occur in NoV.

Recombination within the Pandemic Norovirus GII.4 Lineage

ABSTRACT Norovirus (NoV) is the leading cause of viral gastroenteritis globally. Since 1996, NoV variants of a single genetic lineage, GII.4, have been associated with at least six pandemics of acute gastroenteritis and caused between 62 and 80% of all NoV outbreaks. The emergence of these novel GII.4 variants has been attributed to rapid evolution and antigenic variation in response to herd immunity; however, the contribution of recombination as a mechanism facilitating emergence is increasingly evident. In this study, we sought to examine the role that intragenotype recombination has played in the emergence of GII.4 variants. Using a genome-wide approach including 25 complete genome sequences generated as part of this study, 11 breakpoints were identified within the NoV GII.4 lineage. The breakpoints were located at three recombination hot spots: near the open reading frame 1/2 (ORF1/2) and ORF2/3 overlaps, as well as within ORF2, which encodes the viral capsid, at the junction of the shell and protruding domains. Importantly, we show that recombination contributed to the emergence of the recent pandemic GII.4 variant, New Orleans 2009, and a newly identified GII.4 variant, termed Sydney 2012. Reconstructing the evolutionary history of the GII.4 lineage reveals the widespread impact of both inter- and intragenotype recombination on the emergence of many GII.4 variants. Lastly, this study highlights the many challenges in the identification of true recombination events and proposes that guidelines be applied for identifying NoV recombinants.

The epidemiological fitness cost of drug resistance in Mycobacterium tuberculosis

The emergence of antibiotic resistance in Mycobacterium tuberculosis has raised the concern that pathogen strains that are virtually untreatable may become widespread. The acquisition of resistance to antibiotics results in a longer duration of infection in a host, but this resistance may come at a cost through a decreased transmission rate. This raises the question of whether the overall fitness of drug-resistant strains is higher than that of sensitive strains—essential information for predicting the spread of the disease. Here, we directly estimate the transmission cost of drug resistance, the rate at which resistance evolves, and the relative fitness of resistant strains. These estimates are made by using explicit models of the transmission and evolution of sensitive and resistant strains of M. tuberculosis, using approximate Bayesian computation, and molecular epidemiology data from Cuba, Estonia, and Venezuela. We find that the transmission cost of drug resistance relative to sensitivity can be as low as 10%, that resistance evolves at rates of ≈0.0025–0.02 per case per year, and that the overall fitness of resistant strains is comparable with that of sensitive strains. Furthermore, the contribution of transmission to the spread of drug resistance is very high compared with acquired resistance due to treatment failure (up to 99%). Estimating such parameters directly from in vivo data will be critical to understanding and responding to antibiotic resistance. For instance, projections using our estimates suggest that the prevalence of tuberculosis may decline with successful treatment, but the proportion of cases associated with resistance is likely to increase.

Using Approximate Bayesian Computation to Estimate Tuberculosis Transmission Parameters From Genotype Data

Tuberculosis can be studied at the population level by genotyping strains of Mycobacterium tuberculosis isolated from patients. We use an approximate Bayesian computational method in combination with a stochastic model of tuberculosis transmission and mutation of a molecular marker to estimate the net transmission rate, the doubling time, and the reproductive value of the pathogen. This method is applied to a published data set from San Francisco of tuberculosis genotypes based on the marker IS6110. The mutation rate of this marker has previously been studied, and we use those estimates to form a prior distribution of mutation rates in the inference procedure. The posterior point estimates of the key parameters of interest for these data are as follows: net transmission rate, 0.69/year [95% credibility interval (C.I.) 0.38, 1.08]; doubling time, 1.08 years (95% C.I. 0.64, 1.82); and reproductive value 3.4 (95% C.I. 1.4, 79.7). These figures suggest a rapidly spreading epidemic, consistent with observations of the resurgence of tuberculosis in the United States in the 1980s and 1990s.

The emergence and evolution of the novel epidemic norovirus GII.4 variant Sydney 2012.

Norovirus is the leading cause of acute gastroenteritis with most infections caused by GII.4 variants. To understand the evolutionary processes that contribute to the emergence of GII.4 variants, we examined the molecular epidemiology of norovirus-associated acute gastroenteritis in Australia and New Zealand from 893 outbreaks between 2009 and 2012. Throughout the study GII.4 New Orleans 2009 was predominant; however, during 2012 it was replaced by an emergent GII.4 variant, Sydney 2012. An evolutionary analysis of capsid gene sequences was performed to determine the origins and selective pressures driving the emergence of these recently circulating GII.4 variants. This revealed that both New Orleans 2009 and Sydney 2012 share a common ancestor with GII.4 Apeldoorn 2007. Furthermore, pre-epidemic ancestral variants of each virus were identified up to two years before their pandemic emergence. Adaptive changes at known blockade epitopes in the viral capsid were also identified that likely contributed to their emergence.

Models of deletion for visualizing bacterial variation: an application to tuberculosis spoligotypes

BackgroundMolecular typing methods are commonly used to study genetic relationships among bacterial isolates. Many of these methods have become standardized and produce portable data. A popular approach for analyzing such data is to construct graphs, including phylogenies. Inferences from graph representations of data assist in understanding the patterns of transmission of bacterial pathogens, and basing these graph constructs on biological models of evolution of the molecular marker helps make these inferences. Spoligotyping is a widely used method for genotyping isolates of Mycobacterium tuberculosis that exploits polymorphism in the direct repeat region. Our goal was to examine a range of models describing the evolution of spoligotypes in order to develop a visualization method to represent likely relationships among M. tuberculosis isolates.ResultsWe found that inferred mutations of spoligotypes frequently involve the loss of a single or very few adjacent spacers. Using a second-order variant of Akaikes Information Criterion, we selected the Zipf model as the basis for resolving ambiguities in the ancestry of spoligotypes. We developed a method to construct graphs of spoligotypes (which we call spoligoforests). To demonstrate this method, we applied it to a tuberculosis data set from Cuba and compared the method to some existing methods.ConclusionWe propose a new approach in analyzing relationships of M. tuberculosis isolates using spoligotypes. The spoligoforest recovers a plausible history of transmission and mutation events based on the selected deletion model. The method may be suitable to study markers based on loci of similar structure from other bacteria. The groupings and relationships in the spoligoforest can be analyzed along with the clinical features of strains to provide an understanding of the evolution of spoligotypes.

From traditional medicine to witchcraft: why medical treatments are not always efficacious.

Complementary medicines, traditional remedies and home cures for medical ailments are used extensively world-wide, representing more than US

The Inference of Phased Haplotypes for the Immunoglobulin H Chain V Region Gene Loci by Analysis of VDJ Gene Rearrangements

60 billion sales in the global market. With serious doubts about the efficacy and safety of many treatments, the industry remains steeped in controversy. Little is known about factors affecting the prevalence of efficacious and non-efficacious self-medicative treatments. Here we develop mathematical models which reveal that the most efficacious treatments are not necessarily those most likely to spread. Indeed, purely superstitious remedies, or even maladaptive practices, spread more readily than efficacious treatments under specified circumstances. Low-efficacy practices sometimes spread because their very ineffectiveness results in longer, more salient demonstration and a larger number of converts, which more than compensates for greater rates of abandonment. These models also illuminate a broader range of phenomena, including the spread of innovations, medical treatment of animals, foraging behaviour, and self-medication in non-human primates.

Conditions for the evolution of gene clusters in bacterial genomes

The existence of many highly similar genes in the lymphocyte receptor gene loci makes them difficult to investigate, and the determination of phased “haplotypes” has been particularly problematic. However, V(D)J gene rearrangements provide an opportunity to infer the association of Ig genes along the chromosomes. The chromosomal distribution of H chain genes in an Ig genotype can be inferred through analysis of VDJ rearrangements in individuals who are heterozygous at points within the IGH locus. We analyzed VDJ rearrangements from 44 individuals for whom sufficient unique rearrangements were available to allow comprehensive genotyping. Nine individuals were identified who were heterozygous at the IGHJ6 locus and for whom sufficient suitable VDJ rearrangements were available to allow comprehensive haplotyping. Each of the 18 resulting IGHV│IGHD│IGHJ haplotypes was unique. Apparent deletion polymorphisms were seen that involved as many as four contiguous, functional IGHV genes. Two deletion polymorphisms involving multiple contiguous IGHD genes were also inferred. Three previously unidentified gene duplications were detected, where two sequences recognized as allelic variants of a single gene were both inferred to be on a single chromosome. Phased genomic data brings clarity to the study of the contribution of each gene to the available repertoire of rearranged VDJ genes. Analysis of rearrangement frequencies suggests that particular genes may have substantially different yet predictable propensities for rearrangement within different haplotypes. Together with data highlighting the extent of haplotypic variation within the population, this suggests that there may be substantial variability in the available Ab repertoires of different individuals.