Systematic evaluation of the population-level effects of alternative treatment strategies on the basic reproduction number.

An approach to estimate the influence of the treatment-type controls on the basic reproduction number, R0, is proposed and elaborated. The presented approach allows one to estimate the effect of a given treatment strategy or to compare a number of different treatment strategies on the basic reproduction number. All our results are valid for sufficiently small values of the control. However, in many cases it is possible to extend this analysis to larger values of the control as was illustrated by examples.

Phylogenetically resolving epidemiologic linkage.

Although the use of phylogenetic trees in epidemiological investigations has become commonplace, their epidemiological interpretation has not been systematically evaluated. Here, we use an HIV-1 within-host coalescent model to probabilistically evaluate transmission histories of two epidemiologically linked hosts. Previous critique of phylogenetic reconstruction has claimed that direction of transmission is difficult to infer, and that the existence of unsampled intermediary links or common sources can never be excluded. The phylogenetic relationship between the HIV populations of epidemiologically linked hosts can be classified into six types of trees, based on cladistic relationships and whether the reconstruction is consistent with the true transmission history or not. We show that the direction of transmission and whether unsampled intermediary links or common sources existed make very different predictions about expected phylogenetic relationships: (i) Direction of transmission can often be established when paraphyly exists, (ii) intermediary links can be excluded when multiple lineages were transmitted, and (iii) when the sampled individuals' HIV populations both are monophyletic a common source was likely the origin. Inconsistent results, suggesting the wrong transmission direction, were generally rare. In addition, the expected tree topology also depends on the number of transmitted lineages, the sample size, the time of the sample relative to transmission, and how fast the diversity increases after infection. Typically, 20 or more sequences per subject give robust results. We confirm our theoretical evaluations with analyses of real transmission histories and discuss how our findings should aid in interpreting phylogenetic results.

Notos - a galaxy tool to analyze CpN observed expected ratios for inferring DNA methylation types.

BACKGROUND: DNA methylation patterns store epigenetic information in the vast majority of eukaryotic species. The relatively high costs and technical challenges associated with the detection of DNA methylation however have created a bias in the number of methylation studies towards model organisms. Consequently, it remains challenging to infer kingdom-wide general rules about the functions and evolutionary conservation of DNA methylation. Methylated cytosine is often found in specific CpN dinucleotides, and the frequency distributions of, for instance, CpG observed/expected (CpG o/e) ratios have been used to infer DNA methylation types based on higher mutability of methylated CpG. RESULTS: Predominantly model-based approaches essentially founded on mixtures of Gaussian distributions are currently used to investigate questions related to the number and position of modes of CpG o/e ratios. These approaches require the selection of an appropriate criterion for determining the best model and will fail if empirical distributions are complex or even merely moderately skewed. We use a kernel density estimation (KDE) based technique for robust and precise characterization of complex CpN o/e distributions without a priori assumptions about the underlying distributions. CONCLUSIONS: We show that KDE delivers robust descriptions of CpN o/e distributions. For straightforward processing, we have developed a Galaxy tool, called Notos and available at the ToolShed, that calculates these ratios of input FASTA files and fits a density to their empirical distribution. Based on the estimated density the number and shape of modes of the distribution is determined, providing a rational for the prediction of the number and the types of different methylation classes. Notos is written in R and Perl.

Genetic Variability of Myxoma Virus Genomes.

Myxomatosis is a recurrent problem on rabbit farms throughout Europe despite the success of vaccines. To identify gene variations of field and vaccine strains that may be responsible for changes in virulence, immunomodulation, and immunoprotection, the genomes of 6 myxoma virus (MYXV) strains were sequenced: German field isolates Munich-1, FLI-H, 2604, and 3207; vaccine strain MAV; and challenge strain ZA. The analyzed genomes ranged from 147.6 kb (strain MAV) to 161.8 kb (strain 3207). All sequences were affected by several mutations, covering 24 to 93 open reading frames (ORFs) and resulted in amino acid substitutions, insertions, or deletions. Only strains Munich-1 and MAV revealed the deletion of 10 ORFs (M007L to M015L) and 11 ORFs (M007L to M008.1L and M149R to M008.1R), respectively. Major differences were observed in the 27 immunomodulatory proteins encoded by MYXV. Compared to the reference strain Lausanne, strains FLI-H, 2604, 3207, and ZA showed the highest amino acid identity (>98.4%). In strains Munich-1 and MAV, deletion of 5 and 10 ORFs, respectively, was observed, encoding immunomodulatory proteins with ankyrin repeats or members of the family of serine protease inhibitors. Furthermore, putative immunodominant surface proteins with homology to vaccinia virus (VACV) were investigated in the sequenced strains. Only strain MAV revealed above-average frequencies of amino acid substitutions and frameshift mutations. Finally, we performed recombination analysis and found signs of recombination in vaccine strain MAV. Phylogenetic analysis showed a close relationship of strain MAV and the MSW strain of Californian MYXV. However, in a challenge model, strain MAV provided full protection against lethal challenges with strain ZA. IMPORTANCE: Myxoma virus (MYXV) is pathogenic for European rabbits and two North American species. Due to sophisticated strategies in immune evasion and oncolysis, MYXV is an important model virus for immunological and pathological research. In its natural hosts, MYXV causes a benign infection, whereas in European rabbits, it causes the lethal disease myxomatosis. Since the introduction of MYXV into Australia and Europe for the biological control of European rabbits in the 1950s, a coevolution of host and pathogen has started, selecting for attenuated virus strains and increased resistance in rabbits. Evolution of viruses is a continuous process and influences the protective potential of vaccines. In our analyses, we sequenced 6 MYXV field, challenge, and vaccine strains. We focused on genes encoding proteins involved in virulence, host range, immunomodulation, and envelope composition. Genes affected most by mutations play a role in immunomodulation. However, attenuation cannot be linked to individual mutations or gene disruptions.

Timing and order of transmission events is not directly reflected in a pathogen phylogeny.

Pathogen phylogenies are often used to infer spread among hosts. There is, however, not an exact match between the pathogen phylogeny and the host transmission history. Here, we examine in detail the limitations of this relationship. First, all splits in a pathogen phylogeny of more than 1 host occur within hosts, not at the moment of transmission, predating the transmission events as described by the pretransmission interval. Second, the order in which nodes in a phylogeny occur may be reflective of the within-host dynamics rather than epidemiologic relationships. To investigate these phenomena, motivated by within-host diversity patterns, we developed a two-phase coalescent model that includes a transmission bottleneck followed by linear outgrowth to a maximum population size followed by either stabilization or decline of the population. The model predicts that the pretransmission interval shrinks compared with predictions based on constant population size or a simple transmission bottleneck. Because lineages coalesce faster in a small population, the probability of a pathogen phylogeny to resemble the transmission history depends on when after infection a donor transmits to a new host. We also show that the probability of inferring the incorrect order of multiple transmissions from the same host is high. Finally, we compare time of HIV-1 infection informed by genetic distances in phylogenies to independent biomarker data, and show that, indeed, the pretransmission interval biases phylogeny-based estimates of when transmissions occurred. We describe situations where caution is needed not to misinterpret which parts of a phylogeny that may indicate outbreaks and tight transmission clusters.

A model-based information sharing protocol for profile Hidden Markov Models used for HIV-1 recombination detection.

BACKGROUND: In many applications, a family of nucleotide or protein sequences classified into several subfamilies has to be modeled. Profile Hidden Markov Models (pHMMs) are widely used for this task, modeling each subfamily separately by one pHMM. However, a major drawback of this approach is the difficulty of dealing with subfamilies composed of very few sequences. One of the most crucial bioinformatical tasks affected by the problem of small-size subfamilies is the subtyping of human immunodeficiency virus type 1 (HIV-1) sequences, i.e., HIV-1 subtypes for which only a small number of sequences is known. RESULTS: To deal with small samples for particular subfamilies of HIV-1, we introduce a novel model-based information sharing protocol. It estimates the emission probabilities of the pHMM modeling a particular subfamily not only based on the nucleotide frequencies of the respective subfamily but also incorporating the nucleotide frequencies of all available subfamilies. To this end, the underlying probabilistic model mimics the pattern of commonality and variation between the subtypes with regards to the biological characteristics of HI viruses. In order to implement the proposed protocol, we make use of an existing HMM architecture and its associated inference engine. CONCLUSIONS: We apply the modified algorithm to classify HIV-1 sequence data in the form of partial HIV-1 sequences and semi-artificial recombinants. Thereby, we demonstrate that the performance of pHMMs can be significantly improved by the proposed technique. Moreover, we show that our algorithm performs significantly better than Simplot and Bootscanning.

jpHMM: recombination analysis in viruses with circular genomes such as the hepatitis B virus.

jpHMM is a very accurate and widely used tool for recombination detection in genomic sequences of HIV-1. Here, we present an extension of jpHMM to analyze recombinations in viruses with circular genomes such as the hepatitis B virus (HBV). Sequence analysis of circular genomes is usually performed on linearized sequences using linear models. Since linear models are unable to model dependencies between nucleotides at the 5'- and 3'-end of a sequence, this can result in inaccurate predictions of recombination breakpoints and thus in incorrect classification of viruses with circular genomes. The proposed circular jpHMM takes into account the circularity of the genome and is not biased against recombination breakpoints close to the 5'- or 3'-end of the linearized version of the circular genome. It can be applied automatically to any query sequence without assuming a specific origin for the sequence coordinates. We apply the method to genomic sequences of HBV and visualize its output in a circular form. jpHMM is available online at http://jphmm.gobics.de for download and as a web server for HIV-1 and HBV sequences.

Improving Hidden Markov Models for classification of human immunodeficiency virus-1 subtypes through linear classifier learning.

Profile Hidden Markov Models (pHMMs) are widely used to model nucleotide or protein sequence families. In many applications, a sequence family classified into several subfamilies is given and each subfamily is modeled separately by one pHMM. A major drawback of this approach is the difficulty of coping with subfamilies composed of very few sequences.Correct subtyping of human immunodeficiency virus-1 (HIV-1) sequences is one of the most crucial bioinformatic tasks affected by this problem of small subfamilies, i.e., HIV-1 subtypes with a small number of known sequences. To deal with small samples for particular subfamilies of HIV-1, we employ a machine learning approach. More precisely, we make use of an existing HMM architecture and its associated inference engine, while replacing the unsupervised estimation of emission probabilities by a supervised method. For that purpose, we use regularized linear discriminant learning together with a balancing scheme to account for the widely varying sample size. After training the multiclass linear discriminants, the corresponding weights are transformed to valid probabilities using a softmax function.We apply this modified algorithm to classify HIV-1 sequence data (in the form of partial-length HIV-1 sequences and semi-artificial recombinants) and show that the performance of pHMMs can be significantly improved by the proposed technique.

Genome dynamics in three different geographical isolates of white spot syndrome virus (WSSV).

White spot syndrome virus (WSSV), the sole member of the monotypic family Nimaviridae, is considered an extremely lethal shrimp pathogen. Despite its impact, some essential biological characteristics related to WSSV genome dynamics, such as the synonymous codon usage pattern and selection pressure in genes, remain to be elucidated. The results show that compositional limitations and mutational pressure determine the codon usage bias and base composition in WSSV. Furthermore, different forces of selective pressure are acting across various regions of the WSSV genome. Finally, this study points out the possible occurrence of two major recombination events.

Early life microbial exposures shape the Crassostrea gigas immune system for lifelong and intergenerational disease protection.

BACKGROUND: The interaction of organisms with their surrounding microbial communities influences many biological processes, a notable example of which is the shaping of the immune system in early life. In the Pacific oyster, Crassostrea gigas, the role of the environmental microbial community on immune system maturation - and, importantly, protection from infectious disease - is still an open question. RESULTS: Here, we demonstrate that early life microbial exposure durably improves oyster survival when challenged with the pathogen causing Pacific oyster mortality syndrome (POMS), both in the exposed generation and in the subsequent one. Combining microbiota, transcriptomic, genetic, and epigenetic analyses, we show that the microbial exposure induced changes in epigenetic marks and a reprogramming of immune gene expression leading to long-term and intergenerational immune protection against POMS. CONCLUSIONS: We anticipate that this protection likely extends to additional pathogens and may prove to be an important new strategy for safeguarding oyster aquaculture efforts from infectious disease. tag the videobyte/videoabstract in this section Video Abstract.

Detection of viral sequence fragments of HIV-1 subfamilies yet unknown.

BACKGROUND: Methods of determining whether or not any particular HIV-1 sequence stems - completely or in part - from some unknown HIV-1 subtype are important for the design of vaccines and molecular detection systems, as well as for epidemiological monitoring. Nevertheless, a single algorithm only, the Branching Index (BI), has been developed for this task so far. Moving along the genome of a query sequence in a sliding window, the BI computes a ratio quantifying how closely the query sequence clusters with a subtype clade. In its current version, however, the BI does not provide predicted boundaries of unknown fragments. RESULTS: We have developed Unknown Subtype Finder (USF), an algorithm based on a probabilistic model, which automatically determines which parts of an input sequence originate from a subtype yet unknown. The underlying model is based on a simple profile hidden Markov model (pHMM) for each known subtype and an additional pHMM for an unknown subtype. The emission probabilities of the latter are estimated using the emission frequencies of the known subtypes by means of a (position-wise) probabilistic model for the emergence of new subtypes. We have applied USF to SIV and HIV-1 sequences formerly classified as having emerged from an unknown subtype. Moreover, we have evaluated its performance on artificial HIV-1 recombinants and non-recombinant HIV-1 sequences. The results have been compared with the corresponding results of the BI. CONCLUSIONS: Our results demonstrate that USF is suitable for detecting segments in HIV-1 sequences stemming from yet unknown subtypes. Comparing USF with the BI shows that our algorithm performs as good as the BI or better.

HIV classification using the coalescent theory.

MOTIVATION: Existing coalescent models and phylogenetic tools based on them are not designed for studying the genealogy of sequences like those of HIV, since in HIV recombinants with multiple cross-over points between the parental strains frequently arise. Hence, ambiguous cases in the classification of HIV sequences into subtypes and circulating recombinant forms (CRFs) have been treated with ad hoc methods in lack of tools based on a comprehensive coalescent model accounting for complex recombination patterns. RESULTS: We developed the program ARGUS that scores classifications of sequences into subtypes and recombinant forms. It reconstructs ancestral recombination graphs (ARGs) that reflect the genealogy of the input sequences given a classification hypothesis. An ARG with maximal probability is approximated using a Markov chain Monte Carlo approach. ARGUS was able to distinguish the correct classification with a low error rate from plausible alternative classifications in simulation studies with realistic parameters. We applied our algorithm to decide between two recently debated alternatives in the classification of CRF02 of HIV-1 and find that CRF02 is indeed a recombinant of Subtypes A and G. AVAILABILITY: ARGUS is implemented in C++ and the source code is available at http://gobics.de/software.

jpHMM: improving the reliability of recombination prediction in HIV-1.

Previously, we developed jumping profile hidden Markov model (jpHMM), a new method to detect recombinations in HIV-1 genomes. The jpHMM predicts recombination breakpoints in a query sequence and assigns to each position of the sequence one of the major HIV-1 subtypes. Since incorrect subtype assignment or recombination prediction may lead to wrong conclusions in epidemiological or vaccine research, information about the reliability of the predicted parental subtypes and breakpoint positions is valuable. For this reason, we extended the output of jpHMM to include such information in terms of 'uncertainty' regions in the recombination prediction and an interval estimate of the breakpoint. Both types of information are computed based on the posterior probabilities of the subtypes at each query sequence position. Our results show that this extension strongly improves the reliability of the jpHMM recombination prediction. The jpHMM is available online at http://jphmm.gobics.de/.

Morphological and genomic characterisation of the Schistosoma hybrid infecting humans in Europe reveals admixture between Schistosoma haematobium and Schistosoma bovis.

Schistosomes cause schistosomiasis, the world's second most important parasitic disease after malaria in terms of public health and social-economic impacts. A peculiar feature of these dioecious parasites is their ability to produce viable and fertile hybrid offspring. Originally only present in the tropics, schistosomiasis is now also endemic in southern Europe. Based on the analysis of two genetic markers the European schistosomes had previously been identified as hybrids between the livestock- and the human-infective species Schistosoma bovis and Schistosoma haematobium, respectively. Here, using PacBio long-read sequencing technology we performed genome assembly improvement and annotation of S. bovis, one of the parental species for which no satisfactory genome assembly was available. We then describe the whole genome introgression levels of the hybrid schistosomes, their morphometric parameters (eggs and adult worms) and their compatibility with two European snail strains used as vectors (Bulinus truncatus and Planorbarius metidjensis). Schistosome-snail compatibility is a key parameter for the parasites life cycle progression, and thus the capability of the parasite to establish in a given area. Our results show that this Schistosoma hybrid is strongly introgressed genetically, composed of 77% S. haematobium and 23% S. bovis origin. This genomic admixture suggests an ancient hybridization event and subsequent backcrosses with the human-specific species, S. haematobium, before its introduction in Corsica. We also show that egg morphology (commonly used as a species diagnostic) does not allow for accurate hybrid identification while genetic tests do.

A 20-kb lineage-specific genomic region tames virulence in pathogenic amphidiploid Verticillium longisporum.

Amphidiploid fungal Verticillium longisporum strains Vl43 and Vl32 colonize the plant host Brassica napus but differ in their ability to cause disease symptoms. These strains represent two V. longisporum lineages derived from different hybridization events of haploid parental Verticillium strains. Vl32 and Vl43 carry same-sex mating-type genes derived from both parental lineages. Vl32 and Vl43 similarly colonize and penetrate plant roots, but asymptomatic Vl32 proliferation in planta is lower than virulent Vl43. The highly conserved Vl43 and Vl32 genomes include less than 1% unique genes, and the karyotypes of 15 or 16 chromosomes display changed genetic synteny due to substantial genomic reshuffling. A 20 kb Vl43 lineage-specific (LS) region apparently originating from the Verticillium dahliae-related ancestor is specific for symptomatic Vl43 and encodes seven genes, including two putative transcription factors. Either partial or complete deletion of this LS region in Vl43 did not reduce virulence but led to induction of even more severe disease symptoms in rapeseed. This suggests that the LS insertion in the genome of symptomatic V. longisporum Vl43 mediates virulence-reducing functions, limits damage on the host plant, and therefore tames Vl43 from being even more virulent.

The role of recombination in the emergence of a complex and dynamic HIV epidemic.

BACKGROUND: Inter-subtype recombinants dominate the HIV epidemics in three geographical regions. To better understand the role of HIV recombinants in shaping the current HIV epidemic, we here present the results of a large-scale subtyping analysis of 9435 HIV-1 sequences that involve subtypes A, B, C, G, F and the epidemiologically important recombinants derived from three continents. RESULTS: The circulating recombinant form CRF02_AG, common in West Central Africa, appears to result from recombination events that occurred early in the divergence between subtypes A and G, followed by additional recent recombination events that contribute to the breakpoint pattern defining the current recombinant lineage. This finding also corrects a recent claim that G is a recombinant and a descendant of CRF02, which was suggested to be a pure subtype. The BC and BF recombinants in China and South America, respectively, are derived from recent recombination between contemporary parental lineages. Shared breakpoints in South America BF recombinants indicate that the HIV-1 epidemics in Argentina and Brazil are not independent. Therefore, the contemporary HIV-1 epidemic has recombinant lineages of both ancient and more recent origins. CONCLUSIONS: Taken together, we show that these recombinant lineages, which are highly prevalent in the current HIV epidemic, are a mixture of ancient and recent recombination. The HIV pandemic is moving towards having increasing complexity and higher prevalence of recombinant forms, sometimes existing as "families" of related forms. We find that the classification of some CRF designations need to be revised as a consequence of (1) an estimated > 5% error in the original subtype assignments deposited in the Los Alamos sequence database; (2) an increasing number of CRFs are defined while they do not readily fit into groupings for molecular epidemiology and vaccine design; and (3) a dynamic HIV epidemic context.

Universality of the DNA methylation codes in Eucaryotes.

Genetics and epigenetics are tightly linked heritable information classes. Question arises if epigenetics provides just a set of environment dependent instructions, or whether it is integral part of an inheritance system. We argued that in the latter case the epigenetic code should share the universality quality of the genetic code. We focused on DNA methylation. Since availability of DNA methylation data is biased towards model organisms we developed a method that uses kernel density estimations of CpG observed/expected ratios to infer DNA methylation types in any genome. We show here that our method allows for robust prediction of mosaic and full gene body methylation with a PPV of 1 and 0.87, respectively. We used this prediction to complement experimental data, and applied hierarchical clustering to identify methylation types in ~150 eucaryotic species covering different body plans, reproduction types and living conditions. Our analysis indicates that there are only four gene body methylation types. These types do not follow phylogeny (i.e. phylogenetically distant clades can have identical methylation types) but they are consistent within clades. We conclude that the gene body DNA methylation codes have universality similar to the universality of the genetic code and should consequently be considered as part of the inheritance system.

Correction: Sensitivity of joint contagiousness and susceptibility-based dynamic optimal control strategies for HIV prevention.

[This corrects the article DOI: 10.1371/journal.pone.0204741.].

Dosage Compensation throughout the Schistosoma mansoni Lifecycle: Specific Chromatin Landscape of the Z Chromosome.

Differentiated sex chromosomes are accompanied by a difference in gene dose between X/Z-specific and autosomal genes. At the transcriptomic level, these sex-linked genes can lead to expression imbalance, or gene dosage can be compensated by epigenetic mechanisms and results into expression level equalization. Schistosoma mansoni has been previously described as a ZW species (i.e., female heterogamety, in opposition to XY male heterogametic species) with a partial dosage compensation, but underlying mechanisms are still unexplored. Here, we combine transcriptomic (RNA-Seq) and epigenetic data (ChIP-Seq against H3K4me3, H3K27me3, and H4K20me1 histone marks) in free larval cercariae and intravertebrate parasitic stages. For the first time, we describe differences in dosage compensation status in ZW females, depending on the parasitic status: free cercariae display global dosage compensation, whereas intravertebrate stages show a partial dosage compensation. We also highlight regional differences of gene expression along the Z chromosome in cercariae, but not in the intravertebrate stages. Finally, we feature a consistent permissive chromatin landscape of the Z chromosome in both sexes and stages. We argue that dosage compensation in schistosomes is characterized by chromatin remodeling mechanisms in the Z-specific region.

Sensitivity of joint contagiousness and susceptibility-based dynamic optimal control strategies for HIV prevention.

Predicting the population-level effects of an infectious disease intervention that incorporate multiple modes of intervention is complicated by the joint non-linear dynamics of both infection transmission and the intervention itself. In this paper, we consider the sensitivity of Dynamic Optimal Control Profiles (DOCPs) for the optimal joint investment in both a contagiousness and susceptibility-based control of HIV to bio-behavioral, economic, and programmatic assumptions. The DOCP is calculated using recently developed numerical algorithms that allow controls to be represented by a set of piecewise constant functions that maintain a constant yearly budget. Our transmission model assumes multiple stages of HIV infection corresponding to acute and chronic infection and both within- and between-individual behavioral heterogeneity. We parameterize a baseline scenario from a longitudinal study of sexual behavior in MSM and consider sensitivity of the DOCPs to deviations from that baseline scenario. In the baseline scenario, the primary determinant of the dominant control were programmatic factors, regardless of budget. In sensitivity analyses, the qualitative aspects of the optimal control policy were often robust to significant deviation in assumptions regarding transmission dynamics. In addition, we found several conditions in which long-term joint investment in both interventions was optimal. Our results suggest that modeling in the service of decision support for intervention design can improve population-level effects of a limited set of economic resources. We found that economic and programmatic factors were as important as the inherent transmission dynamics in determining population-level intervention effects. Given our finding that the DOCPs were robust to alternative biological and behavioral assumptions it may be possible to identify DOCPs even when the data are not sufficient to identify a transmission model.