Evolutionary modelling indicates that mosquito metabolism shapes the life-history strategies of Plasmodium parasites.

Within-host survival and between-host transmission are key life-history traits of single-celled malaria parasites. Understanding the evolutionary forces that shape these traits is crucial to predict malaria epidemiology, drug resistance, and virulence. However, very little is known about how Plasmodium parasites adapt to their mosquito vectors. Here, we examine the evolution of the time Plasmodium parasites require to develop within the vector (extrinsic incubation period) with an individual-based model of malaria transmission that includes mosquito metabolism. Specifically, we model the metabolic cascade of resource allocation induced by blood-feeding, as well as the influence of multiple blood meals on parasite development. Our model predicts that successful vector-to-human transmission events are rare, and are caused by long-lived mosquitoes. Importantly, our results show that the life-history strategies of malaria parasites depend on the mosquito's metabolic status. In our model, additional resources provided by multiple blood meals lead to selection for parasites with slow or intermediate developmental time. These results challenge the current assumption that evolution favors fast developing parasites to maximize their chances to complete their within-mosquito life cycle. We propose that the long sporogonic cycle observed for Plasmodium is not a constraint but rather an adaptation to increase transmission potential.

Experimental and computational analyses reveal that environmental restrictions shape HIV-1 spread in 3D cultures.

Pathogens face varying microenvironments in vivo, but suitable experimental systems and analysis tools to dissect how three-dimensional (3D) tissue environments impact pathogen spread are lacking. Here we develop an Integrative method to Study Pathogen spread by Experiment and Computation within Tissue-like 3D cultures (INSPECT-3D), combining quantification of pathogen replication with imaging to study single-cell and cell population dynamics. We apply INSPECT-3D to analyze HIV-1 spread between primary human CD4 T-lymphocytes using collagen as tissue-like 3D-scaffold. Measurements of virus replication, infectivity, diffusion, cellular motility and interactions are combined by mathematical analyses into an integrated spatial infection model to estimate parameters governing HIV-1 spread. This reveals that environmental restrictions limit infection by cell-free virions but promote cell-associated HIV-1 transmission. Experimental validation identifies cell motility and density as essential determinants of efficacy and mode of HIV-1 spread in 3D. INSPECT-3D represents an adaptable method for quantitative time-resolved analyses of 3D pathogen spread.

Mosquito microevolution drives Plasmodium falciparum dynamics.

Malaria, a major cause of child mortality in Africa, is engendered by Plasmodium parasites that are transmitted by anopheline mosquitoes. Fitness of Plasmodium parasites is closely linked to the ecology and evolution of its anopheline vector. However, whether the genetic structure of vector populations impacts malaria transmission remains unknown. Here, we describe a partitioning of the African malaria vectors into generalists and specialists that evolve along ecological boundaries. We next identify the contribution of mosquito species to Plasmodium abundance using Granger causality tests for time-series data collected over two rainy seasons in Mali. We find that mosquito microevolution, defined by changes in the genetic structure of a population over short ecological timescales, drives Plasmodium dynamics in nature, whereas vector abundance, infection prevalence, temperature and rain have low predictive values. Our study demonstrates the power of time-series approaches in vector biology and highlights the importance of focusing local vector control strategies on mosquito species that drive malaria dynamics.

Specificity of inhibitory KIRs enables NK cells to detect changes in an altered peptide environment.

The activity of natural killer (NK) cells is tightly regulated by inhibitory and activating receptors. Inhibitory killer immunoglobulin-like receptors (iKIRs) survey the surface of target cells by monitoring the expression of human leukocyte antigen (HLA) class I. The binding of iKIRs has been shown to be sensitive to the peptides presented by HLA class I, implying that iKIRs have the ability to detect the changes in the repertoire of peptide-HLA class I complexes (pHLA), a process occurring during viral infection and in tumor cells. To study how the pHLA repertoire changes upon infection, and whether an iKIR is able to detect these changes, we study peptides eluted from cells prior and after infection with measles virus (MV). Remarkably, most changes in the repertoire of potential iKIR ligands are predicted to be caused by the altered expression of self-peptides. We show that an iKIR can detect these changes in the presented peptides only if it is sufficiently specific, e.g., if iKIRs can distinguish between different amino acids in the contact residues (e.g., position 7 and 8). Our analysis further indicates that one single iKIR per host is not sufficient to detect changes in the peptide repertoire, suggesting that a multigene family encoding for different iKIRs is required for successful peptide recognition.

Determining Ribavirin's mechanism of action against Lassa virus infection.

Ribavirin is a broad spectrum antiviral which inhibits Lassa virus (LASV) replication in vitro but exhibits a minor effect on viremia in vivo. However, ribavirin significantly improves the disease outcome when administered in combination with sub-optimal doses of favipiravir, a strong antiviral drug. The mechanisms explaining these conflicting findings have not been determined, so far. Here, we used an interdisciplinary approach combining mathematical models and experimental data in LASV-infected mice that were treated with ribavirin alone or in combination with the drug favipiravir to explore different putative mechanisms of action for ribavirin. We test four different hypotheses that have been previously suggested for ribavirin's mode of action: (i) acting as a mutagen, thereby limiting the infectivity of new virions; (ii) reducing viremia by impairing viral production; (iii) modulating cell damage, i.e., by reducing inflammation, and (iv) enhancing antiviral immunity. Our analysis indicates that enhancement of antiviral immunity, as well as effects on viral production or transmission are unlikely to be ribavirin's main mechanism mediating its antiviral effectiveness against LASV infection. Instead, the modeled viral kinetics suggest that the main mode of action of ribavirin is to protect infected cells from dying, possibly reducing the inflammatory response.

The evolution of natural killer cell receptors.

Natural killer (NK) cells are immune cells that play a crucial role against viral infections and tumors. To be tolerant against healthy tissue and simultaneously attack infected cells, the activity of NK cells is tightly regulated by a sophisticated array of germline-encoded activating and inhibiting receptors. The best characterized mechanism of NK cell activation is "missing self" detection, i.e., the recognition of virally infected or transformed cells that reduce their MHC expression to evade cytotoxic T cells. To monitor the expression of MHC-I on target cells, NK cells have monomorphic inhibitory receptors which interact with conserved MHC molecules. However, there are other NK cell receptors (NKRs) encoded by gene families showing a remarkable genetic diversity. Thus, NKR haplotypes contain several genes encoding for receptors with activating and inhibiting signaling, and that vary in gene content and allelic polymorphism. But if missing-self detection can be achieved by a monomorphic NKR system why have these polygenic and polymorphic receptors evolved? Here, we review the expansion of NKR receptor families in different mammal species, and we discuss several hypotheses that possibly underlie the diversification of the NK cell receptor complex, including the evolution of viral decoys, peptide sensitivity, and selective MHC-downregulation.

Can Selective MHC Downregulation Explain the Specificity and Genetic Diversity of NK Cell Receptors?

Natural killer (NK) cells express inhibiting receptors (iNKRs), which specifically bind MHC-I molecules on the surface of healthy cells. When the expression of MHC-I on the cell surface decreases, which might occur during certain viral infections and cancer, iNKRs lose inhibiting signals and the infected cells become target for NK cell activation (missing-self detection). Although the detection of MHC-I deficient cells can be achieved by conserved receptor-ligand interactions, several iNKRs are encoded by gene families with a remarkable genetic diversity, containing many haplotypes varying in gene content and allelic polymorphism. So far, the biological function of this expansion within the NKR cluster has remained poorly understood. Here, we investigate whether the evolution of diverse iNKRs genes can be driven by a specific viral immunoevasive mechanism: selective MHC downregulation. Several viruses, including EBV, CMV, and HIV, decrease the expression of MHC-I to escape from T cell responses. This downregulation does not always affect all MHC loci in the same way, as viruses target particular MHC molecules. To study the selection pressure of selective MHC downregulation on iNKRs, we have developed an agent-based model simulating an evolutionary scenario of hosts infected with herpes-like viruses, which are able to selectively downregulate the expression of MHC-I molecules on the cell surface. We show that iNKRs evolve specificity and, depending on the similarity of MHC alleles within each locus and the differences between the loci, they can specialize to a particular MHC-I locus. The easier it is to classify an MHC allele to its locus, the lower the required diversity of the NKRs. Thus, the diversification of the iNKR cluster depends on the locus specific MHC structure.

A Coevolutionary Arms Race between Hosts and Viruses Drives Polymorphism and Polygenicity of NK Cell Receptors.

Natural killer cell receptors (NKRs) monitor the expression of major histocompatibility class I (MHC-I) and stress molecules to detect unhealthy tissue, such as infected or tumor cells. The NKR gene family shows a remarkable genetic diversity, containing several genes encoding receptors with activating and inhibiting signaling, and varying in gene content and allelic polymorphism. The expansion of the NKR genes is species-specific, with different species evolving alternative expanded NKR genes, which encode structurally different proteins, yet perform comparable functions. So far, the biological function of this expansion within the NKR cluster has remained poorly understood. To study the evolution of NKRs, we have developed an agent-based model implementing a coevolutionary scenario between hosts and herpes-like viruses that are able to evade the immune response by downregulating the expression of MHC-I on the cell surface. We show that hosts evolve specific inhibitory NKRs, specialized to particular MHC-I alleles in the population. Viruses in our simulations readily evolve proteins mimicking the MHC molecules of their host, even in the absence of MHC-I downregulation. As a result, the NKR locus becomes polygenic and polymorphic, encoding both specific inhibiting and activating receptors to optimally protect the hosts from coevolving viruses.

Quantifying the Protection of Activating and Inhibiting NK Cell Receptors during Infection with a CMV-Like Virus.

The responsiveness of natural killer (NK) cells is controlled by balancing signals from activating and inhibitory receptors. The most important ligands of inhibitory NK cell receptors are the highly polymorphic major histocompatibility complex (MHC) class I molecules, which allow NK cells to screen the cellular health of target cells. Although these inhibitory receptor-ligand interactions have been well characterized, the ligands for most activating receptors are still unknown. The mouse cytomegalovirus (MCMV) represents a helpful model to study NK cell-driven immune responses. Many studies have demonstrated that CMV infection can be controlled by NK cells via their activating receptors, but the exact contribution of the different signaling potential (i.e., activating vs. inhibiting) remains puzzling. In this study, we have developed a probabilistic model, which predicts the optimal specificity of inhibitory and activating NK cell receptors needed to offer the best protection against a CMV-like virus. We confirm our analytical predictions with an agent-based model of an evolving host population. Our analysis quantifies the degree of protection of each receptor type, revealing that mixed haplotypes (i.e., haplotypes composed of activating and inhibiting receptors) are most protective against CMV-like viruses, and that the protective effect depends on the number of MHC loci per individual.

Corrigendum: Quantifying the Protection of Activating and Inhibiting NK Cell Receptors during Infection with a CMV-Like Virus.

[This corrects the article on p. 20 in vol. 5, PMID: 24523722.].

Rotor termination is critically dependent on kinetic properties of I kur inhibitors in an in silico model of chronic atrial fibrillation.

Inhibition of the atrial ultra-rapid delayed rectifier potassium current (I Kur) represents a promising therapeutic strategy in the therapy of atrial fibrillation. However, experimental and clinical data on the antiarrhythmic efficacy remain controversial. We tested the hypothesis that antiarrhythmic effects of I Kur inhibitors are dependent on kinetic properties of channel blockade. A mathematical description of I Kur blockade was introduced into Courtemanche-Ramirez-Nattel models of normal and remodeled atrial electrophysiology. Effects of five model compounds with different kinetic properties were analyzed. Although a reduction of dominant frequencies could be observed in two dimensional tissue simulations for all compounds, a reduction of spiral wave activity could be only be detected in two cases. We found that an increase of the percent area of refractory tissue due to a prolongation of the wavelength seems to be particularly important. By automatic tracking of spiral tip movement we find that increased refractoriness resulted in rotor extinction caused by an increased spiral-tip meandering. We show that antiarrhythmic effects of I Kur inhibitors are dependent on kinetic properties of blockade. We find that an increase of the percent area of refractory tissue is the underlying mechanism for an increased spiral-tip meandering, resulting in the extinction of re-entrant circuits.

Virus encoded MHC-like decoys diversify the inhibitory KIR repertoire.

Natural killer (NK) cells are circulating lymphocytes that play an important role in the control of viral infections and tumors. Their functions are regulated by several activating and inhibitory receptors. A subset of these receptors in human NK cells are the killer immunoglobulin-like receptors (KIRs), which interact with the highly polymorphic MHC class I molecules. One important function of NK cells is to detect cells that have down-regulated MHC expression (missing-self). Because MHC molecules have non polymorphic regions, their expression could have been monitored with a limited set of monomorphic receptors. Surprisingly, the KIR family has a remarkable genetic diversity, the function of which remains poorly understood. The mouse cytomegalovirus (MCMV) is able to evade NK cell responses by coding "decoy" molecules that mimic MHC class I. This interaction was suggested to have driven the evolution of novel NK cell receptors. Inspired by the MCMV system, we develop an agent-based model of a host population infected with viruses that are able to evolve MHC down-regulation and decoy molecules. Our simulations show that specific recognition of MHC class I molecules by inhibitory KIRs provides excellent protection against viruses evolving decoys, and that the diversity of inhibitory KIRs will subsequently evolve as a result of the required discrimination between host MHC molecules and decoy molecules.