Phylogenetic analysis accounting for age-dependent death and sampling with applications to epidemics

The reconstruction of phylogenetic trees based on viral genetic sequence data sequentially sampled from an epidemic provides estimates of the past transmission dynamics, by fitting epidemiological models to these trees. To our knowledge, none of the epidemiological models currently used in phylogenetics can account for recovery rates and sampling rates dependent on the time elapsed since transmission. Here we introduce an epidemiological model where infectives leave the epidemic, either by recovery or sampling, after some random time which may follow an arbitrary distribution. We derive an expression for the likelihood of the phylogenetic tree of sampled infectives under our general epidemiological model. The analytic concept developed in this paper will facilitate inference of past epidemiological dynamics and provide an analytical framework for performing very efficient simulations of phylogenetic trees under our model. The main idea of our analytic study is that the non-Markovian epidemiological model giving rise to phylogenetic trees growing vertically as time goes by, can be represented by a Markovian "coalescent point process" growing horizontally by the sequential addition of pairs of coalescence and sampling times. As examples, we discuss two special cases of our general model, namely an application to influenza and an application to HIV. Though phrased in epidemiological terms, our framework can also be used for instance to fit macroevolutionary models to phylogenies of extant and extinct species, accounting for general species lifetime distributions.Comment: 30 pages, 2 figure

Stochastic bacterial population dynamics restrict the establishment of antibiotic resistance from single cells

A better understanding of how antibiotic exposure impacts the evolution of resistance in bacterial populations is crucial for designing more sustainable treatment strategies. The conventional approach to this question is to measure the range of concentrations over which resistant strain(s) are selectively favored over a sensitive strain. Here, we instead investigate how antibiotic concentration impacts the initial establishment of resistance from single cells, mimicking the clonal expansion of a resistant lineage following mutation or horizontal gene transfer. Using two Pseudomonas aeruginosa strains carrying resistance plasmids, we show that single resistant cells have <5% probability of detectable outgrowth at antibiotic concentrations as low as one-eighth of the resistant strain’s minimum inhibitory concentration (MIC). This low probability of establishment is due to detrimental effects of antibiotics on resistant cells, coupled with the inherently stochastic nature of cell division and death on the single-cell level, which leads to loss of many nascent resistant lineages. Our findings suggest that moderate doses of antibiotics, well below the MIC of resistant strains, may effectively restrict de novo emergence of resistance even though they cannot clear already-large resistant populations

TIR-NBS-LRR genes are rare in monocots: evidence from diverse monocot orders

Background: Plant resistance (R) gene products recognize pathogen effector molecules. Many R genes code for proteins containing nucleotide binding site (NBS) and C-terminal leucine-rich repeat (LRR) domains. NBS-LRR proteins can be divided into two groups, TIR-NBS-LRR and non-TIR-NBS-LRR, based on the structure of the N-terminal domain. Although both classes are clearly present in gymnosperms and eudicots, only non-TIR sequences have been found consistently in monocots. Since most studies in monocots have been limited to agriculturally important grasses, it is difficult to draw conclusions. The purpose of our study was to look for evidence of these sequences in additional monocot orders. Findings: Using degenerate PCR, we amplified NBS sequences from four monocot species (C. blanda, D. marginata, S. trifasciata, and Spathiphyllum sp.), a gymnosperm (C. revoluta) and a eudicot (C. canephora). We successfully amplified TIR-NBS-LRR sequences from dicot and gymnosperm DNA, but not from monocot DNA. Using databases, we obtained NBS sequences from additional monocots, magnoliids and basal angiosperms. TIR-type sequences were not present in monocot or magnoliid sequences, but were present in the basal angiosperms. Phylogenetic analysis supported a single TIR clade and multiple non-TIR clades. Conclusion: We were unable to find monocot TIR-NBS-LRR sequences by PCR amplification or database searches. In contrast to previous studies, our results represent five monocot orders (Poales, Zingiberales, Arecales, Asparagales, and Alismatales). Our results establish the presence of TIR-NBS-LRR sequences in basal angiosperms and suggest that although these sequences were present in early land plants, they have been reduced significantly in monocots and magnoliids

TIR-NBS-LRR genes are rare in monocots: evidence from diverse monocot orders

Background: Plant resistance (R) gene products recognize pathogen effector molecules. Many R genes code for proteins containing nucleotide binding site (NBS) and C-terminal leucine-rich repeat (LRR) domains. NBS-LRR proteins can be divided into two groups, TIR-NBS-LRR and non-TIR-NBS-LRR, based on the structure of the N-terminal domain. Although both classes are clearly present in gymnosperms and eudicots, only non-TIR sequences have been found consistently in monocots. Since most studies in monocots have been limited to agriculturally important grasses, it is difficult to draw conclusions. The purpose of our study was to look for evidence of these sequences in additional monocot orders. Findings: Using degenerate PCR, we amplified NBS sequences from four monocot species (C. blanda, D. marginata, S. trifasciata, and Spathiphyllum sp.), a gymnosperm (C. revoluta) and a eudicot (C. canephora). We successfully amplified TIR-NBS-LRR sequences from dicot and gymnosperm DNA, but not from monocot DNA. Using databases, we obtained NBS sequences from additional monocots, magnoliids and basal angiosperms. TIR-type sequences were not present in monocot or magnoliid sequences, but were present in the basal angiosperms. Phylogenetic analysis supported a single TIR clade and multiple non-TIR clades. Conclusion: We were unable to find monocot TIR-NBS-LRR sequences by PCR amplification or database searches. In contrast to previous studies, our results represent five monocot orders (Poales, Zingiberales, Arecales, Asparagales, and Alismatales). Our results establish the presence of TIR-NBS-LRR sequences in basal angiosperms and suggest that although these sequences were present in early land plants, they have been reduced significantly in monocots and magnoliids

THYMUS-DERIVED LYMPHOCYTES PRODUCE AN IMMUNOLOGICALLY SPECIFIC MACROPHAGEARMING FACTOR

Spleen cells from mice immunized with an allogeneic tumor when cultured with the specific tumor cells release into the supernatant a specific macrophage-arming factor(s) (SMAF) which binds nonspecifically to macrophages from both mice and rats and renders these cytotoxic to the specific tumor cells. SMAF also binds in an immunologically specific way to the target cells. SMAF-treated target cells grow normally in the absence of macrophages but are killed in the presence of normal macrophages. Thymus-derived cells are necessary for the production of SMAF since (a) after treatment with anti-θ serum immune spleen cells fail to release SMAF; (b) spleen cells from immunized T cell-deprived mice (thymectomized as adults followed by whole body irradiation and restored with bone marrow) fail to produce SMAF on stimulation with the specific target cells. While SMAF has the properties of a cytophilic antibody, it does not belong to one of the established classes of immunoglobulin since high activity is found after column separation in a fraction having a molecular weight between 50,000–60,000 daltons

Pre-existence and emergence of drug resistance in a generalized model of intra-host viral dynamics

AbstractUnderstanding the source of drug resistance emerging within a treated patient is an important problem, from both clinical and basic evolutionary perspectives. Resistant mutants may arise de novo either before or after treatment is initiated, with different implications for prevention. Here we investigate this problem in the context of chronic viral diseases, such as human immunodeficiency virus (HIV) and hepatitis B and C viruses (HBV and HCV). We present a unified model of viral population dynamics within a host, which can capture a variety of viral life cycles. This allows us to identify which results generalize across various viral diseases, and which are sensitive to the particular virus's life cycle. Accurate analytical approximations are derived that allow for a solid understanding of the parameter dependencies in the system. We find that the mutation-selection balance attained prior to treatment depends on the step at which mutations occur and the viral trait that incurs the cost of resistance. Life cycle effects and key parameters, including mutation rate, infected cell death rate, cost of resistance, and drug efficacy, play a role in determining when mutations arising during treatment are important relative to those pre-existing

Quantifying age-dependent extinction from species phylogenies

International audienceSeveral ecological factors that could play into species extinction are expected to correlate with species age, i.e., time elapsed since the species arose by speciation. To date, however, statistical tools to incorporate species age into likelihood-based phylogenetic inference have been lacking. We present here a computational framework to quantify age-dependent extinction through maximum likelihood parameter estimation based on phylogenetic trees, assuming species lifetimes are gamma distributed. Testing on simulated trees shows that neglecting age dependence can lead to biased estimates of key macroevolutionary parameters. We then apply this method to two real data sets, namely a complete phylogeny of birds (class Aves) and a clade of self-compatible and -incompatible nightshades (Solanaceae), gaining initial insights into the extent to which age-dependent extinction may help explain macroevolutionary patterns. Our methods have been added to the R package TreePar

The traits of "trait ecologists" : An analysis of the use of trait and functional trait terminology

Trait and functional trait approaches have revolutionized ecology improving our understanding of community assembly, species coexistence, and biodiversity loss. Focusing on traits promotes comparability across spatial and organizational scales, but terms must be used consistently. While several papers have offered definitions, it remains unclear how ecologists operationalize "trait" and "functional trait" terms. Here, we evaluate how researchers and the published literatures use these terms and explore differences among subdisciplines and study systems (taxa and biome). By conducting both a survey and a literature review, we test the hypothesis that ecologists' working definition of "trait" is adapted or altered when confronting the realities of collecting, analyzing and presenting data. From 486 survey responses and 712 reviewed papers, we identified inconsistencies in the understanding and use of terminology among researchers, but also limited inclusion of definitions within the published literature. Discrepancies were not explained by subdiscipline, system of study, or respondent characteristics, suggesting there could be an inconsistent understanding even among those working in related topics. Consistencies among survey responses included the use of morphological, phonological, and physiological traits. Previous studies have called for unification of terminology; yet, our study shows that proposed definitions are not consistently used or accepted. Sources of disagreement include trait heritability, defining and interpreting function, and dealing with organisms in which individuals are not clearly recognizable. We discuss and offer guidelines for overcoming these disagreements. The diversity of life on Earth means traits can represent different features that can be measured and reported in different ways, and thus, narrow definitions that work for one system will fail in others. We recommend ecologists embrace the breadth of biodiversity using a simplified definition of "trait" more consistent with its common use. Trait-based approaches will be most powerful if we accept that traits are at least as diverse as trait ecologists.Peer reviewe