Models of immune selection for multi-locus antigenic diversity of pathogens.
Ontology highlight
ABSTRACT:
SUBMITTER: Georgieva M
PROVIDER: S-EPMC6352731 | biostudies-literature | 2019 Jan
REPOSITORIES: biostudies-literature
Publications
Models of immune selection for multi-locus antigenic diversity of pathogens.
Georgieva Maria M Buckee Caroline O CO Lipsitch Marc M
Nature reviews. Immunology 20190101 1
It is well accepted that pathogens can evade recognition and elimination by the host immune system by varying their antigenic targets. Thus, it has become a truism that host immunity is a major driver and determinant of the antigenic diversity of pathogens. However, it remains puzzling how host immunity selects for antigenic diversity at the level of the pathogen population, given that hosts have acquired immune responses to multiple antigens of most pathogens - sometimes through multiple effect ...[more]
Similar Datasets
Project description:Pathogens have evolved diverse strategies to maximize their transmission fitness. Here we investigate these strategies for directly transmitted pathogens using mathematical models of disease pathogenesis and transmission, modeling fitness as a function of within- and between-host pathogen dynamics. The within-host model includes realistic constraints on pathogen replication via resource depletion and cross-immunity between pathogen strains. We find three distinct types of infection emerge as maxima in the fitness landscape, each characterized by particular within-host dynamics, host population contact network structure, and transmission mode. These three infection types are associated with distinct non-overlapping ranges of levels of antigenic diversity, and well-defined patterns of within-host dynamics and between-host transmissibility. Fitness, quantified by the basic reproduction number, also falls within distinct ranges for each infection type. Every type is optimal for certain contact structures over a range of contact rates. Sexually transmitted infections and childhood diseases are identified as exemplar types for low and high contact rates, respectively. This work generates a plausible mechanistic hypothesis for the observed tradeoff between pathogen transmissibility and antigenic diversity, and shows how different classes of pathogens arise evolutionarily as fitness optima for different contact network structures and host contact rates.
| S-EPMC2759524 | biostudies-literature
Project description:The rag locus of Porphyromonas gingivalis W50 encodes RagA, a predicted tonB-dependent receptor protein, and RagB, a lipoprotein that constitutes an immunodominant outer membrane antigen. The low G+C content of the locus, an association with mobility elements, and an apparent restricted distribution in the species suggested that the locus had arisen by horizontal gene transfer. In the present study, we have demonstrated that there are four divergent alleles of the rag locus. The original rag allele found in W50 was renamed rag-1, while three novel alleles, rag-2 to rag-4, were found in isolates lacking rag-1. The three novel alleles encoded variants of RagA with 63 to 71% amino acid identity to RagA1 and each other and variants of RagB with 43 to 56% amino acid identity. The RagA/B proteins have homology to numerous Bacteroides proteins, including SusC/D, implicated in polysaccharide uptake. Monoclonal and polyclonal antibodies raised against RagB1 of P. gingivalis W50 did not cross-react with proteins from isolates carrying different alleles. In a laboratory collection of 168 isolates, 26% carried rag-1, 36% carried rag-2, 25% carried rag-3, and 14% carried rag-4 (including the type strain, ATCC 33277). Restriction profiles of the locus in different isolates demonstrated polymorphism within each allele, some of which is accounted for by the presence or absence of insertion sequence elements. By reference to a previously published study on virulence in a mouse model (M. L. Laine and A. J. van Winkelhoff, Oral Microbiol. Immunol. 13:322-325, 1998), isolates that caused serious disease in mice were significantly more likely to carry rag-1 than other rag alleles.
| S-EPMC1168617 | biostudies-literature
Project description:BackgroundEvidence for genetic contribution to complex diseases is described by recurrence risks to relatives of diseased individuals. Genome-wide association studies allow a description of the genetics of the same diseases in terms of risk loci, their effects and allele frequencies. To reconcile the two descriptions requires a model of how risks from individual loci combine to determine an individual's overall risk.MethodsWe derive predictions of risk to relatives from risks at individual loci under a number of models and compare them with published data on disease risk.ResultsThe model in which risks are multiplicative on the risk scale implies equality between the recurrence risk to monozygotic twins and the square of the recurrence risk to sibs, a relationship often not observed, especially for low prevalence diseases. We show that this theoretical equality is achieved by allowing impossible probabilities of disease. Other models, in which probabilities of disease are constrained to a maximum of one, generate results more consistent with empirical estimates for a range of diseases.ConclusionsThe unconstrained multiplicative model, often used in theoretical studies because of its mathematical tractability, is not a realistic model. We find three models, the constrained multiplicative, Odds (or Logit) and Probit (or liability threshold) models, all fit the data on risk to relatives. Currently, in practice it would be difficult to differentiate between these models, but this may become possible if genetic variants that explain the majority of the genetic variance are identified.
| S-EPMC2847701 | biostudies-literature
Project description:Extensive population-level genetic variability at the Salmonella rfb locus, which encodes enzymes responsible for synthesis of the O-antigen polysaccharide, is thought to have arisen through frequency-dependent selection (FDS) by means of exposure of this pathogen to host immune systems. The FDS hypothesis works well for pathogens such as Haemophilus influenzae and Neisseria meningitis, which alter the composition of their O-antigens during the course of bloodborne infections. In contrast, Salmonella remains resident in epithelial cells or macrophages during infection and does not have phase variability in its O-antigen. More importantly, Salmonella shows host-serovar specificity, whereby strains bearing certain O-antigens cause disease primarily in specific hosts; this behavior is inconsistent with FDS providing selection for the origin or maintenance of extensive polymorphism at the rfb locus. Alternatively, selective pressure may originate from the host intestinal environment itself, wherein diversifying selection mediated by protozoan predation allows for the continued existence of Salmonella able to avoid consumption by host-specific protozoa. This selective pressure would result in high population-level diversity at the Salmonella rfb locus without phase variation. We show here that intestinal protozoa recognize antigenically diverse Salmonella with different efficiencies and demonstrate that differences solely in the O-antigen are sufficient to allow for prey discrimination. Combined with observations of the differential distributions of both serotypes of bacterial species and their protozoan predators among environments, our data provides a framework for the evolution of high genetic diversity at the rfb locus and host-specific pathogenicity in Salmonella.
| S-EPMC489988 | biostudies-literature
Project description:Ehrlichiae are responsible for important tick-transmitted diseases, including anaplasmosis, the most prevalent tick-borne infection of livestock worldwide, and the emerging human diseases monocytic and granulocytic ehrlichiosis. Antigenic variation of major surface proteins is a key feature of these pathogens that allows persistence in the mammalian host, a requisite for subsequent tick transmission. In Anaplasma marginale pseudogenes for two antigenically variable gene families, msp2 and msp3, appear in concert. These pseudogenes can be recombined into the functional expression site to generate new antigenic variants. Coordinated control of the recombination of these genes would allow these two gene families to act synergistically to evade the host immune response.
| S-EPMC31191 | biostudies-literature
Project description:Antimicrobial peptides (AMPs) are part of the inherent immune system. In fact, they occur in almost all organisms including, e.g., plants, animals, and humans. Remarkably, they show effectivity also against multi-resistant pathogens with a high selectivity. This is especially crucial in times, where society is faced with the major threat of an ever-increasing amount of antibiotic resistant microbes. In addition, AMPs can also exhibit antitumor and antiviral effects, thus a variety of scientific studies dealt with the prediction of active peptides in recent years. Due to their potential, even the pharmaceutical industry is keen on discovering and developing novel AMPs. However, AMPs are difficult to verify in vitro, hence researchers conduct sequence similarity experiments against known, active peptides. Unfortunately, this approach is very time-consuming and limits potential candidates to sequences with a high similarity to known AMPs. Machine learning methods offer the opportunity to explore the huge space of sequence variations in a timely manner. These algorithms have, in principal, paved the way for an automated discovery of AMPs. However, machine learning models require a numerical input, thus an informative encoding is very important. Unfortunately, developing an appropriate encoding is a major challenge, which has not been entirely solved so far. For this reason, the development of novel amino acid encodings is established as a stand-alone research branch. The present review introduces state-of-the-art encodings of amino acids as well as their properties in sequence and structure based aggregation. Moreover, albeit a well-chosen encoding is essential, performant classifiers are required, which is reflected by a tendency towards specifically designed models in the literature. Furthermore, we introduce these models with a particular focus on encodings derived from support vector machines and deep learning approaches. Albeit a strong focus has been set on AMP predictions, not all of the mentioned encodings have been elaborated as part of antimicrobial research studies, but rather as general protein or peptide representations.
| S-EPMC6399931 | biostudies-literature
Project description:Individuals from different populations vary considerably in their susceptibility to immune-related diseases. To understand how genetic variation and natural selection contribute to these differences, we tested for the effects of African versus European ancestry on the transcriptional response of primary macrophages to live bacterial pathogens. A total of 9.3% of macrophage-expressed genes show ancestry-associated differences in the gene regulatory response to infection, and African ancestry specifically predicts a stronger inflammatory response and reduced intracellular bacterial growth. A large proportion of these differences are under genetic control: for 804 genes, more than 75% of ancestry effects on the immune response can be explained by a single cis- or trans-acting expression quantitative trait locus (eQTL). Finally, we show that genetic effects on the immune response are strongly enriched for recent, population-specific signatures of adaptation. Together, our results demonstrate how historical selective events continue to shape human phenotypic diversity today, including for traits that are key to controlling infection.
2019-08-29 | GSE136566 | GEO
Project description:Ancient DNA (aDNA) has been a revolutionary technology in understanding human history but has not been used extensively to study natural selection as large sample sizes to study allele frequency changes over time have thus far not been available. Here, we examined a time transect of 708 published samples over the past 7,000 years of European history using multi-locus genotype-based selection scans. As aDNA data is affected by high missingness, ascertainment bias, DNA damage, random allele calling, and is unphased, we first validated our selection scan, G12ancient, on simulated data resembling aDNA under a demographic model that captures broad features of the allele frequency spectrum of European genomes as well as positive controls that have been previously identified and functionally validated in modern European datasets on data from ancient individuals from time periods very close to the present time. We then applied our statistic to the aDNA time transect to detect and resolve the timing of natural selection occurring genome wide and found several candidates of selection across the different time periods that had not been picked up by selection scans using single SNP allele frequency approaches. In addition, enrichment analysis discovered multiple categories of complex traits that might be under adaptation across these periods. Our results demonstrate the utility of applying different types of selection scans to aDNA to uncover putative selection signals at loci in the ancient past that might have been masked in modern samples.
| S-EPMC10168228 | biostudies-literature
Project description:The hypothesis that evolvability - the capacity to evolve by natural selection - is itself the object of natural selection is highly intriguing but remains controversial due in large part to a paucity of direct experimental evidence. The antigenic variation mechanisms of microbial pathogens provide an experimentally tractable system to test whether natural selection has favored mechanisms that increase evolvability. Many antigenic variation systems consist of paralogous unexpressed 'cassettes' that recombine into an expression site to rapidly alter the expressed protein. Importantly, the magnitude of antigenic change is a function of the genetic diversity among the unexpressed cassettes. Thus, evidence that selection favors among-cassette diversity is direct evidence that natural selection promotes antigenic evolvability. We used the Lyme disease bacterium, Borrelia burgdorferi, as a model to test the prediction that natural selection favors amino acid diversity among unexpressed vls cassettes and thereby promotes evolvability in a primary surface antigen, VlsE. The hypothesis that diversity among vls cassettes is favored by natural selection was supported in each B. burgdorferi strain analyzed using both classical (dN/dS ratios) and Bayesian population genetic analyses of genetic sequence data. This hypothesis was also supported by the conservation of highly mutable tandem-repeat structures across B. burgdorferi strains despite a near complete absence of sequence conservation. Diversification among vls cassettes due to natural selection and mutable repeat structures promotes long-term antigenic evolvability of VlsE. These findings provide a direct demonstration that molecular mechanisms that enhance evolvability of surface antigens are an evolutionary adaptation. The molecular evolutionary processes identified here can serve as a model for the evolution of antigenic evolvability in many pathogens which utilize similar strategies to establish chronic infections.
| S-EPMC3828179 | biostudies-literature
Project description:At present, single-trait best linear unbiased prediction (BLUP) is the standard method for genetic selection in soybean. However, when genetic selection is performed based on two or more genetically correlated traits and these are analyzed individually, selection bias may arise. Under these conditions, considering the correlation structure between the evaluated traits may provide more-accurate genetic estimates for the evaluated parameters, even under environmental influences. The present study was thus developed to examine the efficiency and applicability of multi-trait multi-environment (MTME) models by the residual maximum likelihood (REML/BLUP) and Bayesian approaches in the genetic selection of segregating soybean progeny. The study involved data pertaining to 203 soybean F2:4 progeny assessed in two environments for the following traits: number of days to maturity (DM), 100-seed weight (SW), and average seed yield per plot (SY). Variance components and genetic and non-genetic parameters were estimated via the REML/BLUP and Bayesian methods. The variance components estimated and the breeding values and genetic gains predicted with selection through the Bayesian procedure were similar to those obtained by REML/BLUP. The frequentist and Bayesian MTME models provided higher estimates of broad-sense heritability per plot (or heritability of total effects of progeny; [Formula: see text]) and mean accuracy of progeny than their respective single-trait versions. Bayesian analysis provided the credibility intervals for the estimates of [Formula: see text]. Therefore, MTME led to greater predicted gains from selection. On this basis, this procedure can be efficiently applied in the genetic selection of segregating soybean progeny.
| S-EPMC6472761 | biostudies-literature