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Starting at birth, newborn infants are exposed to numerous microorganisms. Adaptation of the innate immune system to them is a delicate process, with potentially advantageous and harmful implications for health development. Cytomegaloviruses (CMVs) are highly adapted to their specific mammalian hosts, with which they share millions of years of co-evolution. Throughout the history of mankind, human CMV has infected most infants in the first months of life without overt implications for health. Thus, CMV infections are intertwined with normal immune development. Nonetheless, CMV has retained substantial pathogenicity following infection or in situations of immunosuppression, leading to pathology in virtually any organ and particularly the central nervous system (CNS). CMVs enter the host through mucosal interfaces of the gastrointestinal and respiratory tract, where macrophages (MACs) are the most abundant immune cell type. Tissue MACs and their potential progenitors, monocytes, are established target cells of CMVs. Recently, several discoveries have revolutionized our understanding on the pre- and postnatal development and site-specific adaptation of tissue MACs. In this review, we explore experimental evidences and concepts on how CMV infections may impact on MAC development and activation as part of host-virus co-adaptation.

Background Bacterial invasive infection and host immune response is fundamental to the understanding of pathogen pathogenesis and the discovery of effective therapeutic drugs. However, there are very few experimental studies on the signaling cross-talks between bacteria and human host to date. Methods In this work, taking M. tuberculosis H37Rv (MTB) that is co-evolving with its human host as an example, we propose a general computational framework that exploits the known bacterial pathogen protein interaction networks in STRING database to predict pathogen-host protein interactions and their signaling cross-talks. In this framework, significant interlogs are derived from the known pathogen protein interaction networks to train a predictive l 2 -regularized logistic regression model. Results The computational results show that the proposed method achieves excellent performance of cross validation as well as low predicted positive rates on the less significant interlogs and non-interlogs, indicating a low risk of false discovery. We further conduct gene ontology (GO) and pathway enrichment analyses of the predicted pathogen-host protein interaction networks, which potentially provides insights into the machinery that M. tuberculosis H37Rv targets human genes and signaling pathways. In addition, we analyse the pathogen-host protein interactions related to drug resistance, inhibition of which potentially provides an alternative solution to M. tuberculosis H37Rv drug resistance. Conclusions The proposed machine learning framework has been verified effective for predicting bacteria-host protein interactions via known bacterial protein interaction networks. For a vast majority of bacterial pathogens that lacks experimental studies of bacteria-host protein interactions, this framework is supposed to achieve a general-purpose applicability. The predicted protein interaction networks between M. tuberculosis H37Rv and Homo sapiens , provided in the Additional files, promise to gain applications in the two fields: (1) providing an alternative solution to drug resistance; (2) revealing the patterns that M. tuberculosis H37Rv genes target human immune signaling pathways.

Some pathogenesis-related genes are expressed in fungi only when the pathogen is in the host, but the host signals that trigger these gene expressions have not been identified. Virulent Nectria haematococca infects pea plants and requires either pelA, which is induced by pectin, or pelD, which is induced only in planta. However, the host signal(s) that trigger pelD expression was unknown. Here we report the isolation of the host signals and identify homoserine and asparagine, two free amino acids found in uniquely high levels in pea seedlings, as the pelD-inducing signals. N. haematococca has evolved a mechanism to sense the host tissue environment by using the high levels of two free amino acids in this plant, thereby triggering the expression of pelD to assist the pathogenic process.

Invasive symbioses between wood-boring insects and fungi are emerging as a new and currently uncontrollable threat to forest ecosystems, as well as fruit and timber industries throughout the world. The bark and ambrosia beetles (Curculionidae: Scolytinae and Platypodinae) constitute the large majority of these pests, and are accompanied by a diverse community of fungal symbionts. Increasingly, some invasive symbioses are shifting from non-pathogenic saprotrophy in native ranges to a prolific tree-killing in invaded ranges, and are causing significant damage. In this paper, we review the current understanding of invasive insect–fungus symbioses. We then ask why some symbioses that evolved as non-pathogenic saprotrophs, turn into major tree-killers in non-native regions. We argue that a purely pathology-centred view of the guild is not sufficient for explaining the lethal encounters between exotic symbionts and naive trees. Instead, we propose several testable hypotheses that, if correct, lead to the conclusion that the sudden emergence of pathogenicity is a new evolutionary phenomenon with global biogeographical dynamics. To date, evidence suggests that virulence of the symbioses in invaded ranges is often triggered when several factors coincide: (i) invasion into territories with naive trees, (ii) the ability of the fungus to either overcome resistance of the naive host or trigger a suicidal over-reaction, and (iii) an ‘olfactory mismatch’ in the insect whereby a subset of live trees is perceived as dead and suitable for colonization. We suggest that individual cases of tree mortality caused by invasive insect–fungus symbionts should no longer be studied separately, but in a global, biogeographically and phylogenetically explicit comparative framework.

Infectious diseases are a major threat for biodiversity conservation and can exert strong influence on wildlife population dynamics. Understanding the mechanisms driving infection rates and epidemic outcomes requires empirical data on the evolutionary trajectory of pathogens and host selective processes. Phylodynamics is a robust framework to understand the interaction of pathogen evolutionary processes with epidemiological dynamics, providing a powerful tool to evaluate disease control strategies. Tasmanian devils have been threatened by a fatal transmissible cancer, devil facial tumour disease (DFTD), for more than two decades. Here we employ a phylodynamic approach using tumour mitochondrial genomes to assess the role of tumour genetic diversity in epidemiological and population dynamics in a devil population subject to 12 years of intensive monitoring, since the beginning of the epidemic outbreak. DFTD molecular clock estimates of disease introduction mirrored observed estimates in the field, and DFTD genetic diversity was positively correlated with estimates of devil population size. However, prevalence and force of infection were the lowest when devil population size and tumour genetic diversity was the highest. This could be due to either differential virulence or transmissibility in tumour lineages or the development of host defence strategies against infection. Our results support the view that evolutionary processes and epidemiological trade‐offs can drive host‐pathogen coexistence, even when disease‐induced mortality is extremely high. We highlight the importance of integrating pathogen and population evolutionary interactions to better understand long‐term epidemic dynamics and evaluating disease control strategies.

Understanding plant–virus coevolution requires wild systems in which there is no human manipulation of either host or virus. To develop such a system, we analysed virus infection in six wild populations of Arabidopsis thaliana in Central Spain. The incidence of five virus species with different life-styles was monitored during four years, and this was analysed in relation to the demography of the host populations. Total virus incidence reached 70 per cent, which suggests a role of virus infection in the population structure and dynamics of the host, under the assumption of a host fitness cost caused by the infection. Maximum incidence occurred at early growth stages, and co-infection with different viruses was frequent, two factors often resulting in increased virulence. Experimental infections under controlled conditions with two isolates of the most prevalent viruses, cauliflower mosaic virus and cucumber mosaic virus, showed that there is genetic variation for virus accumulation, although this depended on the interaction between host and virus genotypes. Comparison of QST-based genetic differentiations between both host populations with FST genetic differentiation based on putatively neutral markers suggests different selection dynamics for resistance against different virus species or genotypes. Together, these results are compatible with a hypothesis of plant–virus coevolution.

Multiple laboratory studies have evolved hosts against a nonevolving pathogen to address questions about evolution of immune responses. However, an ecologically more relevant scenario is one where hosts and pathogens can coevolve. Such coevolution between the antagonists, depending on the mutual selection pressure and additive variance in the respective populations, can potentially lead to a different pattern of evolution in the hosts compared to a situation where the host evolves against a nonevolving pathogen. In the present study, we used Drosophila melanogaster as the host and Pseudomonas entomophila as the pathogen. We let the host populations either evolve against a nonevolving pathogen or coevolve with the same pathogen. We found that the coevolving hosts on average evolved higher survivorship against the coevolving pathogen and ancestral (nonevolving) pathogen relative to the hosts evolving against a nonevolving pathogen. The coevolving pathogens evolved greater ability to induce host mortality even in nonlocal (novel) hosts compared to infection by an ancestral (nonevolving) pathogen. Thus, our results clearly show that the evolved traits in the host and the pathogen under coevolution can be different from one‐sided adaptation. In addition, our results also show that the coevolving host–pathogen interactions can involve certain general mechanisms in the pathogen, leading to increased mortality induction in nonlocal or novel hosts. Evolution of immune responses in a host evolving against a non‐evolving pathogen versus a host coevolving with a pathogen might be different. Using experimental evolution, we show that a coevolving host (Drosophila melanogaster) evolved higher survivorship postinfection with a coevolving or a non‐evolving pathogen (Pseudomonas entomophila) compared to a host that evolved against a non‐evolving pathogen. The coevolving pathogen evolved the ability to induce higher mortality even in non‐local hosts compared to its ancestor.

The Red Queen hypothesis proposes that sex is maintained through selection pressure imposed by coevolving parasites: susceptible hosts are able to escape parasite pressure by recombining their genome to create resistant offspring. However, previous theoretical studies have shown that the Red Queen typically selects against sex unless selection is strong, arguing that high rates of recombination cannot evolve when parasites are of low virulence. Here we show that under the biologically plausible assumption of a severe fitness cost for parasites that fail to infect, the Red Queen can cause selection for high recombination rates, and that the strength of virulence is largely irrelevant to the direction of selection for increased recombination rates. Strong selection on parasites and short generation times make parasites usually better adapted to their hosts than vice versa and can thus favor higher recombination rates in hosts. By demonstrating the importance of host-imposed selection on parasites, our findings resolve previously reported conflicting results.

During my graduate studies, I characterized patterns of geographical distribution and taxonomie differentiation in birds of the West Indies, which suggested that species undergo phases of expansion and contraction similar to the taxon cycles that E. O. Wilson had described for Melanesian ants. Fieldwork in the early 1970s with George Cox confirmed that these phases were associated with variation in habitat distribution and abundance on individual islands, tying together local ecology and biogeography. Because taxon-cycle stage was independent of taxonomic or ecological relationships among birds of the West Indies, George and I postulated that whether a species was in a phase of expansion or contraction reflected the outcome of coevolved relationships with antagonists, including pathogens. The taxon cycle concept had a cool reception initially, but subsequent phylogeographical analyses, beginning in the early 1990s with Eldredge Bermingham, provided a time scale that confirmed the relationship between taxon cycle stage and the relative age of the most recent population expansion. The discrete nature of islands allows one to visualize taxon cycles in island systems, but the principle should apply in a continental biota as well. The absence of strong phylogenetic effects in distribution and abundance is consistent with evolutionary lability caused by coevolutionary outcomes with specialized antagonists. Related species appear to compete for resources on a more-or-less equal footing across a broad range of environments, and their distribution at any particular time is likely to be determined primarily by their relationships with pathogens, among other antagonists. This model of distribution and abundance within a regional community is consistent with much of what we know about the interactions between pathogens and their host populations, but testing the model will require the development of a new research programme focused on endemic pathogen effects in natural communities.

1. The extent to which populations fill available ecological space is critical to evaluating niche-based theories of community assembly, but habitat suitability for populations is difficult to assess. The absence of a species from areas of otherwise suitable habitat might indicate localized species-specific influences, including biological interactions with competitors, consumers or pathogens, on local population persistence. 2. I used Bray—Curtis ordination axis scores, based on the distributions of forest birds across census plots in eastern North America, as proxies of general features of habitat suitability to predict local abundances of each species of small land bird. I then applied spatial analysis to identify significant spatial structure (Moran's I) in residuals (positive or negative) from predicted local densities, which would indicate localized species-specific influences on population size. 3. Fifty-eight of 79 species exhibited no significant spatial structure in residual abundances, indicating that the ordination axes reflect most of the spatial variation in environmental conditions and habitat characteristics that influence population distribution and density or that samples were too small to detect significant spatial variation. Twenty-one species exhibited significant habitat-independent spatial structure of residuals within distances of 100 km. Aggregations of residuals for these species were independently located, for the most part, and thus probably unrelated to general features of the environment that affect many species. 4. Among factors considered as potential causes of spatial anomalies, positive density dependence (Allee effects), intraspecific social aggregation and area sensitivity in response to forest fragmentation find little support in this analysis. Because of the species-specific nature of these clustered residuals, specialized pathogens are potential candidates to drive spatial anomalies in host abundance.