Multilocus Sequence Typing Reveals Extensive Genetic Diversity of the Emerging Fungal Pathogen Scedosporium aurantiacum

Scedosporium spp. are the second most prevalent filamentous fungi after Aspergillus spp. recovered from cystic fibrosis (CF) patients in various regions of the world. Although invasive infection is uncommon prior to lung transplantation, fungal colonization may be a risk factor for invasive disease with attendant high mortality post-transplantation. Abundant in the environment, Scedosporium aurantiacum has emerged as an important fungal pathogen in a range of clinical settings. To investigate the population genetic structure of S. aurantiacum, a MultiLocus Sequence Typing (MLST) scheme was developed, screening 24 genetic loci for polymorphisms on a tester strain set. The six most polymorphic loci were selected to form the S. aurantiacum MLST scheme: actin (ACT), calmodulin (CAL), elongation factor-1α (EF1α), RNA polymerase subunit II (RPB2), manganese superoxide dismutase (SOD2), and β-tubulin (TUB). Among 188 global clinical, veterinary, and environmental strains, 5 to 18 variable sites per locus were revealed, resulting in 8 to 23 alleles per locus. MLST analysis observed a markedly high genetic diversity, reflected by 159 unique sequence types. Network analysis revealed a separation between Australian and non-Australian strains. Phylogenetic analysis showed two major clusters, indicating correlation with geographic origin. Linkage disequilibrium analysis revealed evidence of recombination. There was no clustering according to the source of the strains: clinical, veterinary, or environmental. The high diversity, especially amongst the Australian strains, suggests that S. aurantiacum may have originated within the Australian continent and was subsequently dispersed to other regions, as shown by the close phylogenetic relationships between some of the Australian sequence types and those found in other parts of the world. The MLST data are accessible at http://mlst.mycologylab.org. This is a joined publication of the ISHAM/ECMM working groups on “Scedosporium/Pseudallescheria Infections” and “Fungal Respiratory Infections in Cystic Fibrosis”.

Metapopulation structure modulates sexual antagonism

Despite the far-reaching evolutionary implications of sexual conflict, the effects of metapopulation structure, when populations are subdivided into several demes connected to some degree by migration, on sexual conflict dynamics are unknown. Here, we used experimental evolution in an insect model system, the seed beetle Callosobruchus maculatus, to assess the independent and interacting effects of selection histories associated with mating system (monogamy vs. polygamy) and population subdivision on sexual conflict evolution. We confirm traditional predictions from sexual conflict theory by revealing increased resistance to male harm in females from populations with a history of intense sexual selection (polygamous populations) compared to females from populations with a history of relaxed sexual selection (monogamous populations). However, selection arising from metapopulation structure reversed the classic pattern of sexually antagonistic coevolution and led to reduced resistance in females from polygamous populations. These results underscore that population spatial structure moderates sexual selection and sexual conflict, and more broadly, that the evolution of sexual conflict is contingent on ecological context. The findings also have implications for population dynamics, conservation biology, and biological control.

Functional biology in its natural context: A search for emergent simplicity

The immeasurable complexity at every level of biological organization creates a daunting task for understanding biological function. Here, we highlight the risks of stripping it away at the outset and discuss a possible path toward arriving at emergent simplicity of understanding while still embracing the ever-changing complexity of biotic interactions that we see in nature.

Racial and ethnic comparison of ecological risk factors and youth outcomes: A test of the desensitization hypothesis

Minority youth, because of structural, ecological, and societal inequalities, are at heightened risk of reporting depression and experiencing negative sanctions associated with delinquency. Sociological theories suggest that greater exposure to ecological risk factors at the peer, family, school and community levels are associated with elevated rates of youth depression and delinquency. Desensitization theory posits that repeated exposures to ongoing stressors result in a numbing of psychological and behavioral responses. Thus, it remains unclear whether racial/ethnic differences exist with regards to how contextual stressors correlate with depression and delinquency. Using a sample of 616 Black, 687 Latinx, and 1,318 White youth, this study explores racial/ethnic differences across four ecological risk factors of risky peers, low family warmth, poor school engagement, and community violence as they relate to youth delinquency and depression. Data were collected through in-school survey of youth from 16 public schools surrounding a major city in the Midwest. Significant racial/ethnic differences provided partial support for the desensitization theory. Among Black youth, the magnitude of relationships between ecological risk factors and delinquency was significantly weaker for three of the four predictors and for all four predictors of depression in comparison to White youth. Among Latinx youth, the magnitude of relationships between ecological risk factors was significantly weaker for depression, but not delinquency, in comparison to White youth. Results indicate that ecological risk factors may have differential associations to youth depression and delinquency, which may call for culturally tailored intervention approaches.

Ecological prediction at macroscales using big data: Does sampling design matter?

Although ecosystems respond to global change at regional to continental scales (i.e., macroscales), model predictions of ecosystem responses often rely on data from targeted monitoring of a small proportion of sampled ecosystems within a particular geographic area. In this study, we examined how the sampling strategy used to collect data for such models influences predictive performance. We subsampled a large and spatially extensive data set to investigate how macroscale sampling strategy affects prediction of ecosystem characteristics in 6,784 lakes across a 1.8-million-km² area. We estimated model predictive performance for different subsets of the data set to mimic three common sampling strategies for collecting observations of ecosystem characteristics: random sampling design, stratified random sampling design, and targeted sampling. We found that sampling strategy influenced model predictive performance such that (1) stratified random sampling designs did not improve predictive performance compared to simple random sampling designs and (2) although one of the scenarios that mimicked targeted (non-random) sampling had the poorest performing predictive models, the other targeted sampling scenarios resulted in models with similar predictive performance to that of the random sampling scenarios. Our results suggest that although potential biases in data sets from some forms of targeted sampling may limit predictive performance, compiling existing spatially extensive data sets can result in models with good predictive performance that may inform a wide range of science questions and policy goals related to global change.

LAGOS-NE: a multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of US lakes

Understanding the factors that affect water quality and the ecological services provided by freshwater ecosystems is an urgent global environmental issue. Predicting how water quality will respond to global changes not only requires water quality data, but also information about the ecological context of individual water bodies across broad spatial extents. Because lake water quality is usually sampled in limited geographic regions, often for limited time periods, assessing the environmental controls of water quality requires compilation of many data sets across broad regions and across time into an integrated database. LAGOS-NE accomplishes this goal for lakes in the northeastern-most 17 US states.

LAGOS-NE contains data for 51 101 lakes and reservoirs larger than 4 ha in 17 lake-rich US states. The database includes 3 data modules for: lake location and physical characteristics for all lakes; ecological context (i.e., the land use, geologic, climatic, and hydrologic setting of lakes) for all lakes; and in situ measurements of lake water quality for a subset of the lakes from the past 3 decades for approximately 2600–12 000 lakes depending on the variable. The database contains approximately 150 000 measures of total phosphorus, 200 000 measures of chlorophyll, and 900 000 measures of Secchi depth. The water quality data were compiled from 87 lake water quality data sets from federal, state, tribal, and non-profit agencies, university researchers, and citizen scientists. This database is one of the largest and most comprehensive databases of its type because it includes both in situ measurements and ecological context data. Because ecological context can be used to study a variety of other questions about lakes, streams, and wetlands, this database can also be used as the foundation for other studies of freshwaters at broad spatial and ecological scales.

How to get the most bang for your buck: the evolution and physiology of nutrition-dependent resource allocation strategies

All organisms use resources to grow, survive and reproduce. The supply of these resources varies widely across landscapes and time, imposing ultimate constraints on the maximal trait values for allocation-related traits. In this review, we address three key questions fundamental to our understanding of the evolution of allocation strategies and their underlying mechanisms. First, we ask: how diverse are flexible resource allocation strategies among different organisms? We find there are many, varied, examples of flexible strategies that depend on nutrition. However, this diversity is often ignored in some of the best-known cases of resource allocation shifts, such as the commonly observed pattern of lifespan extension under nutrient limitation. A greater appreciation of the wide variety of flexible allocation strategies leads directly to our second major question: what conditions select for different plastic allocation strategies? Here, we highlight the need for additional models that explicitly consider the evolution of phenotypically plastic allocation strategies and empirical tests of the predictions of those models in natural populations. Finally, we consider the question: what are the underlying mechanisms determining resource allocation strategies? Although evolutionary biologists assume differential allocation of resources is a major factor limiting trait evolution, few proximate mechanisms are known that specifically support the model. We argue that an integrated framework can reconcile evolutionary models with proximate mechanisms that appear at first glance to be in conflict with these models. Overall, we encourage future studies to: (i) mimic ecological conditions in which those patterns evolve, and (ii) take advantage of the 'omic' opportunities to produce multi-level data and analytical models that effectively integrate across physiological and evolutionary theory.

Saccharomyces cerevisiae metabolism in ecological context

The architecture and regulation of Saccharomyces cerevisiae metabolic network are among the best studied owing to its widespread use in both basic research and industry. Yet, several recent studies have revealed notable limitations in explaining genotype-metabolic phenotype relations in this yeast, especially when concerning multiple genetic/environmental perturbations. Apparently unexpected genotype-phenotype relations may originate in the evolutionarily shaped cellular operating principles being hidden in common laboratory conditions. Predecessors of laboratory S. cerevisiae strains, the wild and the domesticated yeasts, have been evolutionarily shaped by highly variable environments, very distinct from laboratory conditions, and most interestingly by social life within microbial communities. Here we present a brief review of the genotypic and phenotypic peculiarities of S. cerevisiae in the context of its social lifestyle beyond laboratory environments. Accounting for this ecological context and the origin of the laboratory strains in experimental design and data analysis would be essential in improving the understanding of genotype-environment-phenotype relationships.