Inferring the dynamics of mutated hematopoietic stem and progenitor cells induced by IFNα in myeloproliferative neoplasms.

Classical BCR-ABL-negative myeloproliferative neoplasms (MPNs) are clonal disorders of hematopoietic stem cells (HSCs) caused mainly by recurrent mutations in genes encoding JAK2 (JAK2), calreticulin (CALR), or the thrombopoietin receptor (MPL). Interferon α (IFNα) has demonstrated some efficacy in inducing molecular remission in MPNs. To determine factors that influence molecular response rate, we evaluated the long-term molecular efficacy of IFNα in patients with MPN by monitoring the fate of cells carrying driver mutations in a prospective observational and longitudinal study of 48 patients over more than 5 years. We measured the clonal architecture of early and late hematopoietic progenitors (84 845 measurements) and the global variant allele frequency in mature cells (409 measurements) several times per year. Using mathematical modeling and hierarchical Bayesian inference, we further inferred the dynamics of IFNα-targeted mutated HSCs. Our data support the hypothesis that IFNα targets JAK2V617F HSCs by inducing their exit from quiescence and differentiation into progenitors. Our observations indicate that treatment efficacy is higher in homozygous than heterozygous JAK2V617F HSCs and increases with high IFNα dose in heterozygous JAK2V617F HSCs. We also found that the molecular responses of CALRm HSCs to IFNα were heterogeneous, varying between type 1 and type 2 CALRm, and a high dose of IFNα correlates with worse outcomes. Our work indicates that the long-term molecular efficacy of IFNα implies an HSC exhaustion mechanism and depends on both the driver mutation type and IFNα dose.

Fighting microbial pathogens by integrating host ecosystem interactions and evolution.

Successful therapies to combat microbial diseases and cancers require incorporating ecological and evolutionary principles. Drawing upon the fields of ecology and evolutionary biology, we present a systems-based approach in which host and disease-causing factors are considered as part of a complex network of interactions, analogous to studies of "classical" ecosystems. Centering this approach around empirical examples of disease treatment, we present evidence that successful therapies invariably engage multiple interactions with other components of the host ecosystem. Many of these factors interact nonlinearly to yield synergistic benefits and curative outcomes. We argue that these synergies and nonlinear feedbacks must be leveraged to improve the study of pathogenesis in situ and to develop more effective therapies. An eco-evolutionary systems perspective has surprising and important consequences, and we use it to articulate areas of high research priority for improving treatment strategies.

Antibiotic stress selects against cooperation in the pathogenic bacterium Pseudomonas aeruginosa.

Cheats are a pervasive threat to public goods production in natural and human communities, as they benefit from the commons without contributing to it. Although ecological antagonisms such as predation, parasitism, competition, and abiotic environmental stress play key roles in shaping population biology, it is unknown how such stresses generally affect the ability of cheats to undermine cooperation. We used theory and experiments to address this question in the pathogenic bacterium, Pseudomonas aeruginosa Although public goods producers were selected against in all populations, our competition experiments showed that antibiotics significantly increased the advantage of nonproducers. Moreover, the dominance of nonproducers in mixed cultures was associated with higher resistance to antibiotics than in either monoculture. Mathematical modeling indicates that accentuated costs to producer phenotypes underlie the observed patterns. Mathematical analysis further shows how these patterns should generalize to other taxa with public goods behaviors. Our findings suggest that explaining the maintenance of cooperative public goods behaviors in certain natural systems will be more challenging than previously thought. Our results also have specific implications for the control of pathogenic bacteria using antibiotics and for understanding natural bacterial ecosystems, where subinhibitory concentrations of antimicrobials frequently occur.

Species dispersal and biodiversity in human-dominated metacommunities.

The concept of the Anthropocene is based on the idea that human impacts are now the primary drivers of changes in the earth's systems, including ecological systems. In many cases, the behavior that causes ecosystem change is itself triggered by ecological factors. Yet most ecological models still treat human impacts as given, and frequently as constant. This undermines our ability to understand the feedbacks between human behavior and ecosystem change. Focusing on the problem of species dispersal, we evaluate the effect of dispersal on biodiversity in a system subject to predation by humans. People are assumed to obtain benefits from (a) the direct consumption of species (provisioning services), (b) the non-consumptive use of species (cultural services), and (c) the buffering effects of the mix of species (regulating services). We find that the effects of dispersal on biodiversity depend jointly on the competitive interactions among species, and on human preferences over species and the services they provide. We find that while biodiversity may be greatest at intermediate levels of dispersal, this depends on structure of preferences across the metacommunity.

A framework for how environment contributes to cancer risk.

Evolutionary theory explains why metazoan species are largely protected against the negative fitness effects of cancers. Nevertheless, cancer is often observed at high incidence across a range of species. Although there are many challenges to quantifying cancer epidemiology and assessing its causes, we claim that most modern-day cancer in animals - and humans in particular - are due to environments deviating from central tendencies of distributions that have prevailed during cancer resistance evolution. Such novel environmental conditions may be natural and/or of anthropogenic origin, and may interface with cancer risk in numerous ways, broadly classifiable as those: increasing organism body size and/or life span, disrupting processes within the organism, and affecting germline. We argue that anthropogenic influences, in particular, explain much of the present-day cancer risk across life, including in humans. Based on a literature survey of animal species and a parameterised mathematical model for humans, we suggest that combined risks of all cancers in a population beyond c. 5% can be explained to some extent by the influence of novel environments. Our framework provides a basis for understanding how natural environmental variation and human activity impact cancer risk, with potential implications for species ecology.

Network structure and local adaptation in co-evolving bacteria-phage interactions.

Numerous theoretical and experimental studies have investigated antagonistic co-evolution between parasites and their hosts. Although experimental tests of theory from a range of biological systems are largely concordant regarding the influence of several driving processes, we know little as to how mechanisms acting at the smallest scales (individual molecular and phenotypic changes) may result in the emergence of structures at larger scales, such as co-evolutionary dynamics and local adaptation. We capitalized on methods commonly employed in community ecology to quantify how the structure of community interaction matrices, so-called bipartite networks, reflected observed co-evolutionary dynamics, and how phages from these communities may or may not have adapted locally to their bacterial hosts. We found a consistent nested network structure for two phage types, one previously demonstrated to exhibit arms race co-evolutionary dynamics and the other fluctuating co-evolutionary dynamics. Both phages increased their host ranges through evolutionary time, but we found no evidence for a trade-off with impact on bacteria. Finally, only bacteria from the arms race phage showed local adaptation, and we provide preliminary evidence that these bacteria underwent (sometimes different) molecular changes in the wzy gene associated with the LPS receptor, while bacteria co-evolving with the fluctuating selection phage did not show local adaptation and had partial deletions of the pilF gene associated with type IV pili. We conclude that the structure of phage-bacteria interaction networks is not necessarily specific to co-evolutionary dynamics, and discuss hypotheses for why only one of the two phages was, nevertheless, locally adapted.

Contrasted coevolutionary dynamics between a bacterial pathogen and its bacteriophages.

Many antagonistic interactions between hosts and their parasites result in coevolution. Although coevolution can drive diversity and specificity within species, it is not known whether coevolutionary dynamics differ among functionally similar species. We present evidence of coevolution within simple communities of Pseudomonas aeruginosa PAO1 and a panel of bacteriophages. Pathogen identity affected coevolutionary dynamics. For five of six phages tested, time-shift assays revealed temporal peaks in bacterial resistance and phage infectivity, consistent with frequency-dependent selection (Red Queen dynamics). Two of the six phages also imposed additional directional selection, resulting in strongly increased resistance ranges over the entire length of the experiment (ca. 60 generations). Cross-resistance to these two phages was very high, independent of the coevolutionary history of the bacteria. We suggest that coevolutionary dynamics are associated with the nature of the receptor used by the phage for infection. Our results shed light on the coevolutionary process in simple communities and have practical application in the control of bacterial pathogens through the evolutionary training of phages, increasing their virulence and efficacy as therapeutics or disinfectants.

Phage selection for bacterial cheats leads to population decline.

While predators and parasites are known for their effects on bacterial population biology, their impact on the dynamics of bacterial social evolution remains largely unclear. Siderophores are iron-chelating molecules that are key to the survival of certain bacterial species in iron-limited environments, but their production can be subject to cheating by non-producing genotypes. In a selection experiment conducted over approximately 20 bacterial generations and involving 140 populations of the pathogenic bacterium Pseudomonas aeruginosa PAO1, we assessed the impact of a lytic phage on competition between siderophore producers and non-producers. We show that the presence of lytic phages favours the non-producing genotype in competition, regardless of whether iron use relies on siderophores. Interestingly, phage pressure resulted in higher siderophore production, which constitutes a cost to the producers and may explain why they were outcompeted by non-producers. By the end of the experiment, however, cheating load reduced the fitness of mixed populations relative to producer monocultures, and only monocultures of producers managed to grow in the presence of phage in situations where siderophores were necessary to access iron. These results suggest that public goods production may be modulated in the presence of natural enemies with consequences for the evolution of social strategies.

Emergence of social complexity among coastal hunter-gatherers in the Atacama Desert of northern Chile.

The emergence of complex cultural practices in simple hunter-gatherer groups poses interesting questions on what drives social complexity and what causes the emergence and disappearance of cultural innovations. Here we analyze the conditions that underlie the emergence of artificial mummification in the Chinchorro culture in the coastal Atacama Desert in northern Chile and southern Peru. We provide empirical and theoretical evidence that artificial mummification appeared during a period of increased coastal freshwater availability and marine productivity, which caused an increase in human population size and accelerated the emergence of cultural innovations, as predicted by recent models of cultural and technological evolution. Under a scenario of increasing population size and extreme aridity (with little or no decomposition of corpses) a simple demographic model shows that dead individuals may have become a significant part of the landscape, creating the conditions for the manipulation of the dead that led to the emergence of complex mortuary practices.

Forecasting antimicrobial resistance evolution.

Antimicrobial resistance (AMR) is a major global health issue. Current measures for tackling it comprise mainly the prudent use of drugs, the development of new drugs, and rapid diagnostics. Relatively little attention has been given to forecasting the evolution of resistance. Here, we argue that forecasting has the potential to be a great asset in our arsenal of measures to tackle AMR. We argue that, if successfully implemented, forecasting resistance will help to resolve the antibiotic crisis in three ways: it will (i) guide a more sustainable use (and therefore lifespan) of antibiotics and incentivize investment in drug development, (ii) reduce the spread of AMR genes and pathogenic microbes in the environment and between patients, and (iii) allow more efficient treatment of persistent infections, reducing the continued evolution of resistance. We identify two important challenges that need to be addressed for the successful establishment of forecasting: (i) the development of bespoke technology that allows stakeholders to empirically assess the risks of resistance evolving during the process of drug development and therapeutic/preventive use, and (ii) the transformative shift in mindset from the current praxis of mostly addressing the problem of antibiotic resistance a posteriori to a concept of a priori estimating, and acting on, the risks of resistance.

Ecological effects of environmental change.

This Special Issue of Ecology Letters presents contributions from an international meeting organised by Centre National de la Recherche Scientifique (CNRS) and Ecology Letters on the broad theme of ecological effects of global environmental change. The objectives of these articles are to synthesise, hypothesise and illustrate the ecological effects of environmental change drivers and their interactions, including habitat loss and fragmentation, pollution, invasive species and climate change. A range of disciplines is represented, including stoichiometry, cell biology, genetics, evolution and biodiversity conservation. The authors emphasise the need to account for several key ecological factors and different spatial and temporal scales in global change research. They also stress the importance of ecosystem complexity through approaches such as functional group and network analyses, and of mechanisms and predictive models with respect to environmental responses to global change across an ecological continuum: population, communities and ecosystems. Lastly, these articles provide important insights and recommendations for environmental conservation and management, as well as highlighting future research priorities.

Quorum sensing as a mechanism to harness the wisdom of the crowds.

Bacteria release and sense small molecules called autoinducers in a process known as quorum sensing. The prevailing interpretation of quorum sensing is that by sensing autoinducer concentrations, bacteria estimate population density to regulate the expression of functions that are only beneficial when carried out by a sufficiently large number of cells. However, a major challenge to this interpretation is that the concentration of autoinducers strongly depends on the environment, often rendering autoinducer-based estimates of cell density unreliable. Here we propose an alternative interpretation of quorum sensing, where bacteria, by releasing and sensing autoinducers, harness social interactions to sense the environment as a collective. Using a computational model we show that this functionality can explain the evolution of quorum sensing and arises from individuals improving their estimation accuracy by pooling many imperfect estimates - analogous to the 'wisdom of the crowds' in decision theory. Importantly, our model reconciles the observed dependence of quorum sensing on both population density and the environment and explains why several quorum sensing systems regulate the production of private goods.

Metastatic cells exploit their stoichiometric niche in the network of cancer ecosystems.

Metastasis is a nonrandom process with varying degrees of organotropism-specific source-acceptor seeding. Understanding how patterns between source and acceptor tumors emerge remains a challenge in oncology. We hypothesize that organotropism results from the macronutrient niche of cells in source and acceptor organs. To test this, we constructed and analyzed a metastatic network based on 9303 records across 28 tissue types. We found that the topology of the network is nested and modular with scale-free degree distributions, reflecting organotropism along a specificity/generality continuum. The variation in topology is significantly explained by the matching of metastatic cells to their stoichiometric niche. Specifically, successful metastases are associated with higher phosphorus content in the acceptor compared to the source organ, due to metabolic constraints in proliferation crucial to the invasion of new tissues. We conclude that metastases are codetermined by processes at source and acceptor organs, where phosphorus content is a limiting factor orchestrating tumor ecology.

Trophic network structure emerges through antagonistic coevolution in temporally varying environments.

Understanding the mechanisms underlying ecological specialization is central to our understanding of community ecology and evolution. Although theoretical work has investigated how variable environments may affect specialization in single species, little is known about how such variation impacts bipartite network structure in antagonistically coevolving systems. Here, we develop and analyse a general model of victim-enemy coevolution that explicitly includes resource and population dynamics. We investigate how temporal environmental heterogeneity affects the evolution of specialization and associated community structure. Environmental productivity influences victim investment in resistance, which will shape patterns of specialization through its regulating effect on enemy investment in infectivity. We also investigate the epidemiological consequences of environmental variability and show that enemy population density is maximized for intermediate lengths of productive seasons, which corresponds to situations where enemies can evolve higher infectivity than victims can evolve defence. We discuss our results in the light of empirical studies, and further highlight ways in which our model applies to a range of natural systems.

Natural resistance to cancers: a Darwinian hypothesis to explain Peto's paradox.

BACKGROUND: Peto's paradox stipulates that there is no association between body mass (a surrogate of number of cells and longevity) and cancer prevalence in wildlife species. Resolving this paradox is a very promising research direction to understand mechanisms of cancer resistance. As of present, research has been focused on the consequences of these evolutionary pressures rather than of their causes. DISCUSSION: Here, we argue that evolution through natural selection may have shaped mechanisms of cancer resistance in wildlife species and that this can result in a threshold in body mass above which oncogenic and tumor suppressive mechanisms should be increasingly purified and positively selected, respectively. SUMMARY: We conclude that assessing wildlife species in their natural ecosystems, especially through theoretical modeling, is the most promising way to understand how evolutionary processes can favor one or the other pathway. This will provide important insights into mechanisms of cancer resistance.

Taylor's Law holds in experimental bacterial populations but competition does not influence the slope.

Populations vary in time and in space, and temporal variation may differ from spatial variation. Yet, in the past half century, field data have confirmed both the temporal and spatial forms of Taylor's power Law, a linear relationship between log(variance) and log(mean) of population size. Recent theory predicted that competitive species interactions should reduce the slope of the temporal version of Taylor's Law. We tested whether this prediction applied to the spatial version of Taylor's Law using simple, well-controlled laboratory populations of two species of bacteria that were cultured either separately or together for 24 h in media of widely varying nutrient richness. Experimentally, the spatial form of Taylor's Law with a slope of 2 held for these simple bacterial communities, but competitive interactions between the two species did not reduce the spatial Taylor's Law slope. These results contribute to the widespread usefulness of Taylor's Law in population ecology, epidemiology and pest control.

Resilience integrates concepts in aging research.

Aging research is unparalleled in the breadth of disciplines it encompasses, from evolutionary studies examining the forces that shape aging to molecular studies uncovering the underlying mechanisms of age-related functional decline. Despite a common focus to advance our understanding of aging, these disciplines have proceeded along distinct paths with little cross-talk. We propose that the concept of resilience can bridge this gap. Resilience describes the ability of a system to respond to perturbations by returning to its original state. Although resilience has been applied in a few individual disciplines in aging research such as frailty and cognitive decline, it has not been explored as a unifying conceptual framework that is able to connect distinct research fields. We argue that because a resilience-based framework can cross broad physiological levels and time scales it can provide the missing links that connect these diverse disciplines. The resulting framework will facilitate predictive modeling and validation and influence targets and directions in research on the biology of aging.

Species coexistence in a variable world.

The contribution of deterministic and stochastic processes to species coexistence is widely debated. With the introduction of powerful statistical techniques, we can now better characterise different sources of uncertainty when quantifying niche differentiation. The theoretical literature on the effect of stochasticity on coexistence, however, is often ignored by field ecologists because of its technical nature and difficulties in its application. In this review, we examine how different sources of variability in population dynamics contribute to coexistence. Unfortunately, few general rules emerge among the different models that have been studied to date. Nonetheless, we believe that a greater understanding is possible, based on the integration of coexistence and population extinction risk theories. There are two conditions for coexistence in the presence of environmental and demographic variability: (1) the average per capita growth rates of all coexisting species must be positive when at low densities, and (2) these growth rates must be strong enough to overcome negative random events potentially pushing densities to extinction. We propose that critical tests for species coexistence must account for niche differentiation arising from this variability and should be based explicitly on notions of stability and ecological drift.

A conceptual framework for the evolution of ecological specialisation.

Ecology Letters (2011) 14: 841-851 ABSTRACT: Ecological specialisation concerns all species and underlies many major ecological and evolutionary patterns. Yet its status as a unifying concept is not always appreciated because of its similarity to concepts of the niche, the many levels of biological phenomena to which it applies, and the complexity of the mechanisms influencing it. The evolution of specialisation requires the coupling of constraints on adaptive evolution with covariation of genotype and environmental performance. This covariation itself depends upon organismal properties such as dispersal behaviour and life history and complexity in the environment stemming from factors such as species interactions and spatio-temporal heterogeneity in resources. Here, we develop a view on specialisation that integrates across the range of biological phenomena with the goal of developing a more predictive conceptual framework that specifically accounts for the importance of biotic complexity and coevolutionary events.