Dataset Information

Restif2006 - Whooping cough

ABSTRACT: Restif2006 - Whooping cough This model is described in the article: Integrating life history and cross-immunity into the evolutionary dynamics of pathogens. Restif O, Grenfell BT. Proc. Biol. Sci. 2006 Feb; 273(1585): 409-416 Abstract: Models for the diversity and evolution of pathogens have branched into two main directions: the adaptive dynamics of quantitative life-history traits (notably virulence) and the maintenance and invasion of multiple, antigenically diverse strains that interact with the host's immune memory. In a first attempt to reconcile these two approaches, we developed a simple modelling framework where two strains of pathogens, defined by a pair of life-history traits (infectious period and infectivity), interfere through a given level of cross-immunity. We used whooping cough as a potential example, but the framework proposed here could be applied to other acute infectious diseases. Specifically, we analysed the effects of these parameters on the invasion dynamics of one strain into a population, where the second strain is endemic. Whereas the deterministic version of the model converges towards stable coexistence of the two strains in most cases, stochastic simulations showed that transient epidemic dynamics can cause the extinction of either strain. Thus ecological dynamics, modulated by the immune parameters, eventually determine the adaptive value of different pathogen genotypes. We advocate an integrative view of pathogen dynamics at the crossroads of immunology, epidemiology and evolution, as a way towards efficient control of infectious diseases. This version of the model can be used for both the stochastic and the deterministic simulations described in the article. For deterministic interpretations with infinite population sizes, set the population size N = 1. The model reproduces the deterministic time courses. Stochastic interpretation with Copasi UI gave results similar to the article, but was not extensively tested. The initial conditions for competition simulations can be derived by equilibrating the system for one pathogen and then adding a starting concentration for the other. Originally created by libAntimony v1.3 (using libSBML 4.1.0-b1) This model is hosted on BioModels Database and identified by: BIOMD0000000249. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

DISEASE(S): Pertussis

SUBMITTER: Lukas Endler

PROVIDER: BIOMD0000000249 | BioModels | 2010-04-21

REPOSITORIES: BioModels

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Publications

Integrating life history and cross-immunity into the evolutionary dynamics of pathogens.

Restif Olivier O Grenfell Bryan T BT

Proceedings. Biological sciences 20060201 1585

Models for the diversity and evolution of pathogens have branched into two main directions: the adaptive dynamics of quantitative life-history traits (notably virulence) and the maintenance and invasion of multiple, antigenically diverse strains that interact with the host's immune memory. In a first attempt to reconcile these two approaches, we developed a simple modelling framework where two strains of pathogens, defined by a pair of life-history traits (infectious period and infectivity), int ...[more]

PMID: 16615206

Publication: 1/3

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Project description:Restif2007 - Vaccination invasion This model is described in the article: Vaccination and the dynamics of immune evasion. Restif O, Grenfell BT. J R Soc Interface 2007 Feb; 4(12): 143-153 Abstract: Vaccines exert strong selective pressures on pathogens, favouring the spread of antigenic variants. We propose a simple mathematical model to investigate the dynamics of a novel pathogenic strain that emerges in a population where a previous strain is maintained at low endemic level by a vaccine. We compare three methods to assess the ability of the novel strain to invade and persist: algebraic rate of invasion; deterministic dynamics; and stochastic dynamics. These three techniques provide complementary predictions on the fate of the system. In particular, we emphasize the importance of stochastic simulations, which account for the possibility of extinctions of either strain. More specifically, our model suggests that the probability of persistence of an invasive strain (i) can be minimized for intermediate levels of vaccine cross-protection (i.e. immune protection against the novel strain) and (ii) is lower if cross-immunity acts through a reduced infectious period rather than through reduced susceptibility. This version of the model can be used for both the stochastic and the deterministic simulations described in the article. For deterministic interpretations with infinite population sizes, set the population size N = 1. The model does reproduces the deterministic time course. The initial values are set to the steady state values for a latent infection with strain 1 with an invading infection of strain 2 (I2=1e-06), 100 percent vaccination with a susceptibility reduction τ=0.7 at birth (p=1), and all other parameters as in figure 3 of the publication. To be compatible with older software tools, the english letter names instead of the greek symbols were used for parameter names: parameter symbol name transmission rate β beta recovery rate γ gamma birth/death rate μ mu rate of loss of natural immunity σ sigma rate of loss of vaccine immunity σ v sigmaV reduction of susceptibility by primary infection θ theta reduction of infection period by primary infection ν nu reduction of susceptibility by vaccination τ tau reduction of infection period by vaccination η eta Originally created by libAntimony v1.4 (using libSBML 3.4.1) This model is hosted on BioModels Database and identified by: BIOMD0000000294. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Both prokaryotic and eukaryotic organisms take deterministic decisions to reprogram cell fates. A macroscopic manifestation of such an event is the remodelling of the cellsâ morphology and it typically is governed at the molecular scale by massive reorganization of the cellular transcriptome. With the regulation at the level of transcription initiation representing the most common form for such developmental reprogramming, cells typically rely on one or several master regulators to coordinate the the activity of hundreds of genes simultaneously by directly binding to their promoters. Despite the apparent simplicity of prokaryotes and their reduced genome size compared to that of their eukaryotic counterparts, free-living bacteria typically encode hundreds of transcription factors (TFs) in their genomes that could act as master TFs. By contrast, obligate intracellular bacteria such as Chlamydiae have a drastically reduced genome due to their intimate association with the host and thus a smaller number of TF genes. The genomes of members of the Chlamydiaceae family, which include the well-known bacterial pathogens Chlamydia trachomatis and Chlamydia pneumoniae, are only 1-1.2 Mbp. By contrast, members of the environmental Chlamydiae Waddlia chondrophila and Parachlamydia acanthamoebae have a 2-fold and 3-fold larger genome, respectively, likely allowing for an expansion of the host range while still retaining their host dependence and parasitic life style. Moreover, they all exhibit a characteristic chlamydial developmental cycle via two functionally specialized morphotypes, the infectious non-dividing elementary bodies (EBs) and the non-infectious dividing reticulate bodies (RBs). This developmental cycle is usually divided in three stages: the early stage during which EBs enter host cells and differentiate into RBs; the mid-stage where RBs proliferate inside a vacuole called inclusion and the late stage where RBs differentiate back into EBs and are released after exocytosis or cell lysis. Chlamydial genes are thus classified into three different temporal classes (early, mid and late expressed genes), likely reflecting the need of these transcripts in each of the three developmental stages. W. chondrophila, an emerging pathogen implicated in abortion in bovine and miscarriage in humans, encodes less than 20 TFs, 10 of which are conserved among the Chlamydiae. In light of this low TF multiplicity in the chlamydial pan-genome along with the common developmental cycle and parasitic life style, we aimed to define the regulatory pan-genome of each these conserved TFs to identify the elusive chlamydial master regulator and to characterize underling specificity for its target promoters using chromatin-immunoprecipitation followed by deep-sequencing (ChIP-Seq) of chlamydial cells growing inside the host. The immunochemistry of ChIP-Seq has the advantage of minimizing the contaminating nucleic acids compared to chlamydial transcriptome studies, it has the added benefit of providing the first unambiguous glimpse into the regulatory landscape of a bacterium inside host, offering a solid framework in understanding the stochastic and/or deterministic switches that bacteria rely on during infections. Examination of the regulatory network of an intracellular pathogen

Project description:<p>The study of antimicrobial resistance (AMR) in infectious diarrhea has generally been limited to cultivation, antimicrobial susceptibility testing and targeted PCR assays. When individual strains of significance are identified, whole genome shotgun (WGS) sequencing of important clones and clades is performed. Genes that encode resistance to antibiotics have been detected in environmental, insect, human and animal metagenomes and are known as "resistomes". While metagenomic datasets have been mined to characterize the healthy human gut resistome in the Human Microbiome Project and MetaHIT and in a Yanomani Amerindian cohort, directed metagenomic sequencing has not been used to examine the epidemiology of AMR. Especially in developing countries where sanitation is poor, diarrhea and enteric pathogens likely serve to disseminate antibiotic resistance elements of clinical significance. Unregulated use of antibiotics further exacerbates the problem by selection for acquisition of resistance. This is exemplified by recent reports of multiple antibiotic resistance in Shigella strains in India, in Escherichia coli in India and Pakistan, and in nontyphoidal Salmonella (NTS) in South-East Asia. We propose to use deep metagenomic sequencing and genome level assembly to study the epidemiology of AMR in stools of children suffering from diarrhea. Here the epidemiology component will be surveillance and analysis of the microbial composition (to the bacterial species/strain level where possible) and its constituent antimicrobial resistance genetic elements (such as plasmids, integrons, transposons and other mobile genetic elements, or MGEs) in samples from a cohort where diarrhea is prevalent and antibiotic exposure is endemic. The goal will be to assess whether consortia of specific mobile antimicrobial resistance elements associate with species/strains and whether their presence is enhanced or amplified in diarrheal microbiomes and in the presence of antibiotic exposure. This work could potentially identify clonal complexes of organisms and MGEs with enhanced resistance and the potential to transfer this resistance to other enteric pathogens.</p> <p>We have performed WGS, metagenomic assembly and gene/protein mapping to examine and characterize the types of AMR genes and transfer elements (transposons, integrons, bacteriophage, plasmids) and their distribution in bacterial species and strains assembled from DNA isolated from diarrheal and non-diarrheal stools. The samples were acquired from a cohort of pediatric patients and controls from Colombia, South America where antibiotic use is prevalent. As a control, the distribution and abundance of AMR genes can be compared to published studies where resistome gene lists from healthy cohort sequences were compiled. Our approach is more epidemiologic in nature, as we plan to identify and catalogue antimicrobial elements on MGEs capable of spread through a local population and further we will, where possible, link mobile antimicrobial resistance elements with specific strains within the population.</p>

Dataset Information

Restif2006 - Whooping cough

Publications

Integrating life history and cross-immunity into the evolutionary dynamics of pathogens.

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