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Developing general principles of host–microorganism interactions necessitates a robust understanding of the eco-evolutionary processes that structure microbiota. Phylosymbiosis, or patterns of microbiome composition that can be predicted by host phylogeny, is a unique framework for interrogating these processes. Identifying the contexts in which phylosymbiosis does and does not occur facilitates an evaluation of the relative importance of different ecological processes in shaping the microbial community. In this Review, we summarize the prevalence of phylosymbiosis across the animal kingdom on the basis of the current literature and explore the microbial community assembly processes and related host traits that contribute to phylosymbiosis. We find that phylosymbiosis is less prevalent in taxonomically richer microbiomes and hypothesize that this pattern is a result of increased stochasticity in the assembly of complex microbial communities. We also note that despite hosting rich microbiomes, mammals commonly exhibit phylosymbiosis. We hypothesize that this pattern is a result of a unique combination of mammalian traits, including viviparous birth, lactation and the co-evolution of haemochorial placentas and the eutherian immune system, which compound to ensure deterministic microbial community assembly. Examining both the individual and the combined importance of these traits in driving phylosymbiosis provides a new framework for research in this area moving forward.In this Review, Mallott and Amato summarize the prevalence of phylosymbiosis across the animal kingdom and explore the microbial community assembly processes and related host traits that contribute to phylosymbiosis. They find that phylosymbiosis is less prevalent in taxonomically richer microbiomes across the animal kingdom, except in mammals, perhaps owing to a unique combination of mammalian traits that influence the microbiota.

Abstract Lactobacillus species are found in nutrient-rich habitats associated with food, feed, plants, animals and humans. Due to their economic importance, the metabolism, genetics and phylogeny of lactobacilli have been extensively studied. However, past research primarily examined lactobacilli in experimental settings abstracted from any natural history, and the ecological context in which these bacteria exist and evolve has received less attention. In this review, we synthesize phylogenetic, genomic and metabolic metadata of the Lactobacillus genus with findings from fine-scale phylogenetic and functional analyses of representative species to elucidate the evolution and natural history of its members. The available evidence indicates a high level of niche conservatism within the well-supported phylogenetic groups within the genus, with lifestyles ranging from free-living to strictly symbiotic. The findings are consistent with a model in which host-adapted Lactobacillus lineages evolved from free-living ancestors, with present-day species displaying substantial variations in terms of the reliance on environmental niches and the degree of host specificity. This model can provide a framework for the elucidation of the natural and evolutionary history of Lactobacillus species and valuable information to improve the use of this important genus in industrial and therapeutic applications. This review synthesizes phylogenetic, genomic and metabolic metadata with findings from ecological and population genetic studies to elucidate the natural history of species within the Lactobacillus genus. Based on this analysis, a model for the evolution of distinct lifestyles was proposed: lifestyles of lactobacilli range from free living to strictly host adapted, with substantial variation among species in terms of the reliance on environmental niches and the degree of host specificity.

Wheat blast first emerged in Brazil in the mid-1980s and has recently caused heavy crop losses in Asia. Here we show how this devastating pathogen evolved in Brazil. Genetic analysis of host species determinants in the blast fungus resulted in the cloning of avirulence genes PWT3 and PWT4, whose gene products elicit defense in wheat cultivars containing the corresponding resistance genes Rwt3 and Rwt4. Studies on avirulence and resistance gene distributions, together with historical data on wheat cultivation in Brazil, suggest that wheat blast emerged due to widespread deployment of rwt3 wheat (susceptible to Lolium isolates), followed by the loss of function of PWT3. This implies that the rwt3 wheat served as a springboard for the host jump to common wheat.

Infectious diseases of domesticated animals impact human well-being via food insecurity, loss of livelihoods, and human infections. While much research has focused on parasites that infect single host species, most parasites of domesticated mammals infect multiple species. The impact of multihost parasites varies across hosts; some rarely result in death, whereas others are nearly always fatal. Despite their high ecological and societal costs, we currently lack theory for predicting the lethality of multihost parasites. Here, using a global dataset of >4,000 case-fatality rates for 65 infectious diseases (caused by microparasites and macroparasites) and 12 domesticated host species, we show that the average evolutionary distance from an infected host to other mammal host species is a strong predictor of disease-induced mortality. We find that as parasites infect species outside of their documented phylogenetic host range, they are more likely to result in lethal infections, with the odds of death doubling for each additional 10 million years of evolutionary distance. Our results for domesticated animal diseases reveal patterns in the evolution of highly lethal parasites that are difficult to observe in the wild and further suggest that the severity of infectious diseases may be predicted from evolutionary relationships among hosts.

Gilliamella apicola and Snodgrassella alvi are dominant members of the honey bee (Apis spp.) and bumble bee (Bombus spp.) gut microbiota. We generated complete genomes of the type strains G. apicola wkB1 ᵀ and S. alvi wkB2 ᵀ (isolated from Apis), as well as draft genomes for four other strains from Bombus . G. apicola and S. alvi were found to occupy very different metabolic niches: The former is a saccharolytic fermenter, whereas the latter is an oxidizer of carboxylic acids. Together, they may form a syntrophic network for partitioning of metabolic resources. Both species possessed numerous genes [type 6 secretion systems, repeats in toxin (RTX) toxins, RHS proteins, adhesins, and type IV pili] that likely mediate cell–cell interactions and gut colonization. Variation in these genes could account for the host fidelity of strains observed in previous phylogenetic studies. Here, we also show the first experimental evidence, to our knowledge, for this specificity in vivo: Strains of S. alvi were able to colonize their native bee host but not bees of another genus. Consistent with specific, long-term host association, comparative genomic analysis revealed a deep divergence and little or no gene flow between Apis and Bombus gut symbionts. However, within a host type (Apis or Bombus), we detected signs of horizontal gene transfer between G. apicola and S. alvi , demonstrating the importance of the broader gut community in shaping the evolution of any one member. Our results show that host specificity is likely driven by multiple factors, including direct host–microbe interactions, microbe–microbe interactions, and social transmission.

Nowadays, bacteriophages are increasingly considered as an alternative treatment for a variety of bacterial infections in cases where classical antibiotics have become ineffective. However, characterizing the host specificity of phages remains a labor- and time-intensive process. In order to alleviate this burden, we have developed a new machine-learning-based pipeline to predict bacteriophage hosts based on annotated receptor-binding protein (RBP) sequence data. We focus on predicting bacterial hosts from the ESKAPE group, Escherichia coli , Salmonella enterica and Clostridium difficile . We compare the performance of our predictive model with that of the widely used Basic Local Alignment Search Tool (BLAST). Our best-performing predictive model reaches Precision-Recall Area Under the Curve (PR-AUC) scores between 73.6 and 93.8% for different levels of sequence similarity in the collected data. Our model reaches a performance comparable to that of BLASTp when sequence similarity in the data is high and starts outperforming BLASTp when sequence similarity drops below 75%. Therefore, our machine learning methods can be especially useful in settings in which sequence similarity to other known sequences is low. Predicting the hosts of novel metagenomic RBP sequences could extend our toolbox to tune the host spectrum of phages or phage tail-like bacteriocins by swapping RBPs.

Genome-wide association studies have the potential to identify causal genetic factors underlying important phenotypes but have rarely been performed in bacteria. We present an association mapping method that takes into account the clonal population structure of bacteria and is applicable to both core and accessory genome variation. Campylobacter is a common cause of human gastroenteritis as a consequence of its proliferation in multiple farm animal species and its transmission via contaminated meat and poultry. We applied our association mapping method to identify the factors responsible for adaptation to cattle and chickens among 192 Campylobacter isolates from these and other host sources. Phylogenetic analysis implied frequent host switching but also showed that some lineages were strongly associated with particular hosts. A seven-gene region with a host association signal was found. Genes in this region were almost universally present in cattle but were frequently absent in isolates from chickens and wild birds. Three of the seven genes encoded vitamin B ₅ biosynthesis. We found that isolates from cattle were better able to grow in vitamin B ₅-depleted media and propose that this difference may be an adaptation to host diet.

Mosquitoes with null mutations in the orco olfactory co-receptor have reduced preference for humans, are only attracted to human odour in the presence of CO 2 and are not repelled by the odour of the insect repellent DEET. How to put mosquitos off the scent The most dangerous vectors of human disease, such as Anopheles gambiae and Aedes aegypti , differ from less-threating types by having a strong preference for human blood as opposed to a broader diet of vertebrate blood. How mosquitoes distinguish humans from non-humans is not understood. Here Leslie Vosshall and colleagues have developed gene-targeting in A. aegypti mosquitoes to produce mutant females that retain a strong attraction to both human and animal hosts in the presence of carbon dioxide (the exhaled gas acts as an attractant) but no longer prefer humans. The mutation disrupts the orco gene, which codes for a co-receptor that is essential for all insect odorant receptors. Interestingly the orco -mutant female mosquitoes were attracted to humans even in the presence of the insect repellant DEET, although they were repelled upon contact. This indicates that there are both olfactory- and contact-mediated effects of DEET. Female mosquitoes of some species are generalists and will blood-feed on a variety of vertebrate hosts, whereas others display marked host preference. Anopheles gambiae and Aedes aegypti have evolved a strong preference for humans, making them dangerously efficient vectors of malaria and Dengue haemorrhagic fever 1 . Specific host odours probably drive this strong preference because other attractive cues, including body heat and exhaled carbon dioxide (CO 2 ), are common to all warm-blooded hosts 2 , 3 . Insects sense odours via several chemosensory receptor families, including the odorant receptors (ORs), membrane proteins that form heteromeric odour-gated ion channels 4 , 5 comprising a variable ligand-selective subunit and an obligate co-receptor called Orco (ref. 6 ). Here we use zinc-finger nucleases to generate targeted mutations in the orco gene of A. aegypti to examine the contribution of Orco and the odorant receptor pathway to mosquito host selection and sensitivity to the insect repellent DEET ( N , N -diethyl-meta-toluamide). orco mutant olfactory sensory neurons have greatly reduced spontaneous activity and lack odour-evoked responses. Behaviourally, orco mutant mosquitoes have severely reduced attraction to honey, an odour cue related to floral nectar, and do not respond to human scent in the absence of CO 2 . However, in the presence of CO 2 , female orco mutant mosquitoes retain strong attraction to both human and animal hosts, but no longer strongly prefer humans. orco mutant females are attracted to human hosts even in the presence of DEET, but are repelled upon contact, indicating that olfactory- and contact-mediated effects of DEET are mechanistically distinct. We conclude that the odorant receptor pathway is crucial for an anthropophilic vector mosquito to discriminate human from non-human hosts and to be effectively repelled by volatile DEET.

Nonhost resistance to plant pathogens can be constitutive or induced by microbes. Successful pathogens suppress microbe-induced plant defences by delivering appropriate effectors, which are apparently not sufficiently effective on nonhost plant species, as can be concluded from the strong host specificity of many biotroph plant pathogens. Such effectors act on particular plant targets, such as promoters or motifs in expressed sequences. Despite much progress in the elucidation of the molecular aspects of nonhost resistance to plant pathogens, very little is known about the genes that determine whether effectors can or cannot suppress the basal defence. In hosts they can, in nonhosts they cannot. The targets determining the host status of plants can be identified in inheritance studies. Recent reports have indicated that nonhost resistance is inherited polygenically, and exhibits strong similarity and association with the basal resistance of plants to adapted pathogens.

Geographic and taxonomic host ranges determine the distribution of biotrophic organisms. Host phylogenetic distance strongly affects the community composition of pathogens and parasites, but little is known about the host phylogeny effect on communities of mutualists, such as plant–pollinator and plant–mycorrhizal fungi systems. By incorporating phylogenetic eigenvectors into univariate and multivariate models, we aimed to determine the relative contribution of host phylogeny and environmental variables to mycorrhizal traits and community composition of ectomycorrhizal (EcM) fungi in Salicaceae at the local scale. Host phylogeny explained 75% of the variation in fungal species richness and 20% of the variation in community composition. We also re‐analyzed a system involving eight hosts from Japan, in which host phylogeny explained 26% and 9% of the variation in fungal richness and community composition, respectively. [Correction added after online publication 21 May 2013: in the preceding sentence the values 9% and 26% have been transposed.] Phylogenetic eigenvectors that differentially account for clades and terminal taxa across the phylogeny revealed stronger host effects than did the treatment of host species as categorical or dummy variables in multiregression models, and in comparison with methods such as Mantel test and its analogs. Our results indicate the usefulness of the eigenvector method for the quantification of the host phylogeny effect, which represents an integrated complex function of taxonomic sampling effect and phylogenetic distance per se.