Host resources and parasite traits interact to determine the optimal combination of host parasite-mitigation strategies.

Organisms have evolved diverse strategies to manage parasite infections. Broadly, hosts may avoid infection by altering behaviour, resist infection by targeting parasites or tolerate infection by repairing associated damage. The effectiveness of a strategy depends on interactions between, for example, resource availability, parasite traits (virulence, life-history) and the host itself (nutritional status, immunopathology). To understand how these factors shape host parasite-mitigation strategies, we developed a mathematical model of within-host, parasite-immune dynamics in the context of helminth infections. The model incorporated host nutrition and resource allocation to different mechanisms of immune response: larval parasite prevention; adult parasite clearance; damage repair (tolerance). We also considered a non-immune strategy: avoidance via anorexia, reducing intake of infective stages. Resources not allocated to immune processes promoted host condition, whereas harm due to parasites and immunopathology diminished it. Maximising condition (a proxy for fitness), we determined optimal host investment for each parasite-mitigation strategy, singly and combined, across different environmental resource levels and parasite trait values. Which strategy was optimal varied with scenario. Tolerance generally performed well, especially with high resources. Success of the different resistance strategies (larval prevention or adult clearance) tracked relative virulence of larval and adult parasites: slowly maturing, highly damaging larvae favoured prevention; rapidly maturing, less harmful larvae favoured clearance. Anorexia was viable only in the short term, due to reduced host nutrition. Combined strategies always outperformed any lone strategy: these were dominated by tolerance, with some investment in resistance. Choice of parasite mitigation strategy has profound consequences for hosts, impacting their condition, survival and reproductive success. We show that the efficacy of different strategies is highly dependent on timescale, parasite traits and resource availability. Models that integrate such factors can inform the collection and interpretation of empirical data, to understand how those drivers interact to shape host immune responses in natural systems.

A mixed-model approach for estimating drivers of microbiota community composition and differential taxonomic abundance.

Next-generation sequencing (NGS) and metabarcoding approaches are increasingly applied to wild animal populations, but there is a disconnect between the widely applied generalized linear mixed model (GLMM) approaches commonly used to study phenotypic variation and the statistical toolkit from community ecology typically applied to metabarcoding data. Here, we describe the suitability of a novel GLMM-based approach for analyzing the taxon-specific sequence read counts derived from standard metabarcoding data. This approach allows decomposition of the contribution of different drivers to variation in community composition (e.g., age, season, individual) via interaction terms in the model random-effects structure. We provide guidance to implementing this approach and show how these models can identify how responsible specific taxonomic groups are for the effects attributed to different drivers. We applied this approach to two cross-sectional data sets from the Soay sheep population of St. Kilda. GLMMs showed agreement with dissimilarity-based approaches highlighting the substantial contribution of age and minimal contribution of season to microbiota community compositions, and simultaneously estimated the contribution of other technical and biological factors. We further used model predictions to show that age effects were principally due to increases in taxa of the phylum Bacteroidetes and declines in taxa of the phylum Firmicutes. This approach offers a powerful means for understanding the influence of drivers of community structure derived from metabarcoding data. We discuss how our approach could be readily adapted to allow researchers to estimate contributions of additional factors such as host or microbe phylogeny to answer emerging questions surrounding the ecological and evolutionary roles of within-host communities. IMPORTANCE NGS and fecal metabarcoding methods have provided powerful opportunities to study the wild gut microbiome. A wealth of data is, therefore, amassing across wild systems, generating the need for analytical approaches that can appropriately investigate simultaneous factors at the host and environmental scale that determine the composition of these communities. Here, we describe a generalized linear mixed-effects model (GLMM) approach to analyze read count data from metabarcoding of the gut microbiota, allowing us to quantify the contributions of multiple host and environmental factors to within-host community structure. Our approach provides outputs that are familiar to a majority of field ecologists and can be run using any standard mixed-effects modeling packages. We illustrate this approach using two metabarcoding data sets from the Soay sheep population of St. Kilda investigating age and season effects as worked examples.

Secrets of the Hospital Underbelly: Patterns of Abundance of Antimicrobial Resistance Genes in Hospital Wastewater Vary by Specific Antimicrobial and Bacterial Family.

Background: Hospital wastewater is a major source of antimicrobial resistance (AMR) outflow into the environment. This study uses metagenomics to study how hospital clinical activity impacts antimicrobial resistance genes (ARGs) abundances in hospital wastewater. Methods: Sewage was collected over a 24-h period from multiple wastewater collection points (CPs) representing different specialties within a tertiary hospital site and simultaneously from community sewage works. High throughput shotgun sequencing was performed using Illumina HiSeq4000. ARG abundances were correlated to hospital antimicrobial usage (AMU), data on clinical activity and resistance prevalence in clinical isolates. Results: Microbiota and ARG composition varied between CPs and overall ARG abundance was higher in hospital wastewater than in community influent. ARG and microbiota compositions were correlated (Procrustes analysis, p=0.014). Total antimicrobial usage was not associated with higher ARG abundance in wastewater. However, there was a small positive association between resistance genes and antimicrobial usage matched to ARG phenotype (IRR 1.11, CI 1.06-1.16, p<0.001). Furthermore, analyzing carbapenem and vancomycin resistance separately indicated that counts of ARGs to these antimicrobials were positively associated with their increased usage [carbapenem rate ratio (RR) 1.91, 95% CI 1.01-3.72, p=0.07, and vancomycin RR 10.25, CI 2.32-49.10, p<0.01]. Overall, ARG abundance within hospital wastewater did not reflect resistance patterns in clinical isolates from concurrent hospital inpatients. However, for clinical isolates of the family Enterococcaceae and Staphylococcaceae, there was a positive relationship with wastewater ARG abundance [odds ratio (OR) 1.62, CI 1.33-2.00, p<0.001, and OR 1.65, CI 1.21-2.30, p=0.006 respectively]. Conclusion: We found that the relationship between hospital wastewater ARGs and antimicrobial usage or clinical isolate resistance varies by specific antimicrobial and bacterial family studied. One explanation, we consider is that relationships observed from multiple departments within a single hospital site will be detectable only for ARGs against parenteral antimicrobials uniquely used in the hospital setting. Our work highlights that using metagenomics to identify the full range of ARGs in hospital wastewater is a useful surveillance tool to monitor hospital ARG carriage and outflow and guide environmental policy on AMR.

Pathogen Dynamics across the Diversity of Aging.

AbstractReproduction, mortality, and immune function often change with age but do not invariably deteriorate. Across the tree of life, there is extensive variation in age-specific performance and changes to key life-history traits. These changes occur on a spectrum from classic senescence, where performance declines with age, to juvenescence, where performance improves with age. Reproduction, mortality, and immune function are also important factors influencing the spread of infectious disease, yet there exists no comprehensive investigation into how the aging spectrum of these traits impacts epidemics. We used a model laboratory infection system to compile an aging profile of a single organism, including traits directly linked to pathogen susceptibility and those that should indirectly alter pathogen transmission by influencing demography. We then developed generalizable epidemiological models demonstrating that different patterns of aging produce dramatically different transmission landscapes: in many cases, aging can reduce the probability of epidemics, but it can also promote severity. This work provides context and tools for use across taxa by empiricists, demographers, and epidemiologists, advancing our ability to accurately predict factors contributing to epidemics or the potential repercussions of senescence manipulation.

Kin selection explains the evolution of cooperation in the gut microbiota.

Through the secretion of "public goods" molecules, microbes cooperatively exploit their habitat. This is known as a major driver of the functioning of microbial communities, including in human disease. Understanding why microbial species cooperate is therefore crucial to achieve successful microbial community management, such as microbiome manipulation. A leading explanation is that of Hamilton's inclusive-fitness framework. A cooperator can indirectly transmit its genes by helping the reproduction of an individual carrying similar genes. Therefore, all else being equal, as relatedness among individuals increases, so should cooperation. However, the predictive power of relatedness, particularly in microbes, is surrounded by controversy. Using phylogenetic comparative analyses across the full diversity of the human gut microbiota and six forms of cooperation, we find that relatedness is predictive of the cooperative gene content evolution in gut-microbe genomes. Hence, relatedness is predictive of cooperation over broad microbial taxonomic levels that encompass variation in other life-history and ecology details. This supports the generality of Hamilton's central insights and the relevance of relatedness as a key parameter of interest to advance microbial predictive and engineering science.

Global monitoring of antimicrobial resistance based on metagenomics analyses of urban sewage.

Antimicrobial resistance (AMR) is a serious threat to global public health, but obtaining representative data on AMR for healthy human populations is difficult. Here, we use metagenomic analysis of untreated sewage to characterize the bacterial resistome from 79 sites in 60 countries. We find systematic differences in abundance and diversity of AMR genes between Europe/North-America/Oceania and Africa/Asia/South-America. Antimicrobial use data and bacterial taxonomy only explains a minor part of the AMR variation that we observe. We find no evidence for cross-selection between antimicrobial classes, or for effect of air travel between sites. However, AMR gene abundance strongly correlates with socio-economic, health and environmental factors, which we use to predict AMR gene abundances in all countries in the world. Our findings suggest that global AMR gene diversity and abundance vary by region, and that improving sanitation and health could potentially limit the global burden of AMR. We propose metagenomic analysis of sewage as an ethically acceptable and economically feasible approach for continuous global surveillance and prediction of AMR.

Division of Labor, Bet Hedging, and the Evolution of Mixed Biofilm Investment Strategies.

Bacterial cells, like many other organisms, face a tradeoff between longevity and fecundity. Planktonic cells are fast growing and fragile, while biofilm cells are often slower growing but stress resistant. Here we ask why bacterial lineages invest simultaneously in both fast- and slow-growing types. We develop a population dynamic model of lineage expansion across a patchy environment and find that mixed investment is favored across a broad range of environmental conditions, even when transmission is entirely via biofilm cells. This mixed strategy is favored because of a division of labor where exponentially dividing planktonic cells can act as an engine for the production of future biofilm cells, which grow more slowly. We use experimental evolution to test our predictions and show that phenotypic heterogeneity is persistent even under selection for purely planktonic or purely biofilm transmission. Furthermore, simulations suggest that maintenance of a biofilm subpopulation serves as a cost-effective hedge against environmental uncertainty, which is also consistent with our experimental findings.IMPORTANCE Cell types specialized for survival have been observed and described within clonal bacterial populations for decades, but why are these specialists continually produced under benign conditions when such investment comes at a high reproductive cost? Conversely, when survival becomes an imperative, does it ever benefit the population to maintain a pool of rapidly growing but vulnerable planktonic cells? Using a combination of mathematical modeling, simulations, and experiments, we find that mixed investment strategies are favored over a broad range of environmental conditions and rely on a division of labor between cell types, where reproductive specialists amplify survival specialists, which can be transmitted through the environment with a limited mortality rate. We also show that survival specialists benefit rapidly growing populations by serving as a hedge against unpredictable changes in the environment. These results help to clarify the general evolutionary and ecological forces that can generate and maintain diverse subtypes within clonal bacterial populations.

Environmental modification via a quorum sensing molecule influences the social landscape of siderophore production.

Bacteria produce a wide variety of exoproducts that favourably modify their environment and increase their fitness. These are often termed 'public goods' because they are costly for individuals to produce and can be exploited by non-producers (cheats). The outcome of conflict over public goods is dependent upon the prevailing environment and the phenotype of the individuals in competition. Many bacterial species use quorum sensing (QS) signalling molecules to regulate the production of public goods. QS, therefore, determines the cooperative phenotype of individuals, and influences conflict over public goods. In addition to their regulatory functions, many QS molecules have additional properties that directly modify the prevailing environment. This leads to the possibility that QS molecules could influence conflict over public goods indirectly through non-signalling effects, and the impact of this on social competition has not previously been explored. The Pseudomonas aeruginosa QS signal molecule PQS is a powerful chelator of iron which can cause an iron starvation response. Here, we show that PQS stimulates a concentration-dependent increase in the cooperative production of iron scavenging siderophores, resulting in an increase in the relative fitness of non-producing siderophore cheats. This is likely due to an increased cost of siderophore output by producing cells and a concurrent increase in the shared benefits, which accrue to both producers and cheats. Although PQS can be a beneficial signalling molecule for P. aeruginosa, our data suggest that it can also render a siderophore-producing population vulnerable to competition from cheating strains. More generally, our results indicate that the production of one social trait can indirectly affect the costs and benefits of another social trait.

Disease spread in age structured populations with maternal age effects.

Fundamental ecological processes, such as extrinsic mortality, determine population age structure. This influences disease spread when individuals of different ages differ in susceptibility or when maternal age determines offspring susceptibility. We show that Daphnia magna offspring born to young mothers are more susceptible than those born to older mothers, and consider this alongside previous observations that susceptibility declines with age in this system. We used a susceptible-infected compartmental model to investigate how age-specific susceptibility and maternal age effects on offspring susceptibility interact with demographic factors affecting disease spread. Our results show a scenario where an increase in extrinsic mortality drives an increase in transmission potential. Thus, we identify a realistic context in which age effects and maternal effects produce conditions favouring disease transmission.

Killing by Type VI secretion drives genetic phase separation and correlates with increased cooperation.

By nature of their small size, dense growth and frequent need for extracellular metabolism, microbes face persistent public goods dilemmas. Genetic assortment is the only general solution stabilizing cooperation, but all known mechanisms structuring microbial populations depend on the availability of free space, an often unrealistic constraint. Here we describe a class of self-organization that operates within densely packed bacterial populations. Through mathematical modelling and experiments with Vibrio cholerae, we show how killing adjacent competitors via the Type VI secretion system (T6SS) precipitates phase separation via the 'Model A' universality class of order-disorder transition mediated by killing. We mathematically demonstrate that T6SS-mediated killing should favour the evolution of public goods cooperation, and empirically support this prediction using a phylogenetic comparative analysis. This work illustrates the twin role played by the T6SS, dealing death to local competitors while simultaneously creating conditions potentially favouring the evolution of cooperation with kin.

Beyond killing: Can we find new ways to manage infection?

The antibiotic pipeline is running dry and infectious disease remains a major threat to public health. An efficient strategy to stay ahead of rapidly adapting pathogens should include approaches that replace, complement or enhance the effect of both current and novel antimicrobial compounds. In recent years, a number of innovative approaches to manage disease without the aid of traditional antibiotics and without eliminating the pathogens directly have emerged. These include disabling pathogen virulence-factors, increasing host tissue damage control or altering the microbiota to provide colonization resistance, immune resistance or disease tolerance against pathogens. We discuss the therapeutic potential of these approaches and examine their possible consequences for pathogen evolution. To guarantee a longer half-life of these alternatives to directly killing pathogens, and to gain a full understanding of their population-level consequences, we encourage future work to incorporate evolutionary perspectives into the development of these treatments.

Quorum sensing protects bacterial co-operation from exploitation by cheats.

Quorum sensing (QS) is a cell-cell communication system found in many bacterial species, commonly controlling secreted co-operative traits, including extracellular digestive enzymes. We show that the canonical QS regulatory architecture allows bacteria to sense the genotypic composition of high-density populations, and limit co-operative investments to social environments enriched for co-operators. Using high-density populations of the opportunistic pathogen Pseudomonas aeruginosa we map per-capita signal and co-operative enzyme investment in the wild type as a function of the frequency of non-responder cheats. We demonstrate mathematically and experimentally that the observed response rule of 'co-operate when surrounded by co-operators' allows bacteria to match their investment in co-operation to the composition of the group, therefore allowing the maintenance of co-operation at lower levels of population structuring (that is, lower relatedness). Similar behavioural responses have been described in vertebrates under the banner of 'generalised reciprocity'. Our results suggest that mechanisms of reciprocity are not confined to taxa with advanced cognition, and can be implemented at the cellular level via positive feedback circuits.

The biogeography of polymicrobial infection.

Microbial communities are spatially organized in both the environment and the human body. Although patterns exhibited by these communities are described by microbial biogeography, this discipline has previously only considered large-scale, global patterns. By contrast, the fine-scale positioning of a pathogen within an infection site can greatly alter its virulence potential. In this Review, we highlight the importance of considering spatial positioning in the study of polymicrobial infections and discuss targeting biogeography as a therapeutic strategy.

Single gene locus changes perturb complex microbial communities as much as apex predator loss.

Many bacterial species are highly social, adaptively shaping their local environment through the production of secreted molecules. This can, in turn, alter interaction strengths among species and modify community composition. However, the relative importance of such behaviours in determining the structure of complex communities is unknown. Here we show that single-locus changes affecting biofilm formation phenotypes in Bacillus subtilis modify community structure to the same extent as loss of an apex predator and even to a greater extent than loss of B. subtilis itself. These results, from experimentally manipulated multitrophic microcosm assemblages, demonstrate that bacterial social traits are key modulators of the structure of their communities. Moreover, they show that intraspecific genetic variability can be as important as strong trophic interactions in determining community dynamics. Microevolution may therefore be as important as species extinctions in shaping the response of microbial communities to environmental change.

Building the microbiome in health and disease: niche construction and social conflict in bacteria.

Microbes collectively shape their environment in remarkable ways via the products of their metabolism. The diverse environmental impacts of macro-organisms have been collated and reviewed under the banner of 'niche construction'. Here, we identify and review a series of broad and overlapping classes of bacterial niche construction, ranging from biofilm production to detoxification or release of toxins, enzymes, metabolites and viruses, and review their role in shaping microbiome composition, human health and disease. Some bacterial niche-constructing traits can be seen as extended phenotypes, where individuals actively tailor their environment to their benefit (and potentially to the benefit of others, generating social dilemmas). Other modifications can be viewed as non-adaptive by-products from a producer perspective, yet they may lead to remarkable within-host environmental changes. We illustrate how social evolution and niche construction perspectives offer complementary insights into the dynamics and consequences of these traits across distinct timescales. This review highlights that by understanding the coupled bacterial and biochemical dynamics in human health and disease we can better manage host health.

The relative efficiency of modular and non-modular networks of different size.

Most biological networks are modular but previous work with small model networks has indicated that modularity does not necessarily lead to increased functional efficiency. Most biological networks are large, however, and here we examine the relative functional efficiency of modular and non-modular neural networks at a range of sizes. We conduct a detailed analysis of efficiency in networks of two size classes: 'small' and 'large', and a less detailed analysis across a range of network sizes. The former analysis reveals that while the modular network is less efficient than one of the two non-modular networks considered when networks are small, it is usually equally or more efficient than both non-modular networks when networks are large. The latter analysis shows that in networks of small to intermediate size, modular networks are much more efficient that non-modular networks of the same (low) connective density. If connective density must be kept low to reduce energy needs for example, this could promote modularity. We have shown how relative functionality/performance scales with network size, but the precise nature of evolutionary relationship between network size and prevalence of modularity will depend on the costs of connectivity.

Vultures acquire information on carcass location from scavenging eagles.

Vultures are recognized as the scroungers of the natural world, owing to their ecological role as obligate scavengers. While it is well known that vultures use intraspecific social information as they forage, the possibility of inter-guild social information transfer and the resulting multi-species social dilemmas has not been explored. Here, we use data on arrival times at carcasses to show that such social information transfer occurs, with raptors acting as producers of information and vultures acting as scroungers of information. We develop a game-theoretic model to show that competitive asymmetry, whereby vultures dominate raptors at carcasses, predicts this evolutionary outcome. We support this theoretical prediction using empirical data from competitive interactions at carcasses. Finally, we use an individual-based model to show that these producer-scrounger dynamics lead to vultures being vulnerable to declines in raptor populations. Our results show that social information transfer can lead to important non-trophic interactions among species and highlight important potential links among social evolution, community ecology and conservation biology. With vulture populations suffering global declines, our study underscores the importance of ecosystem-based management for these endangered keystone species.