Putting evolution in elimination

Putting evolution in elimination

Resistance, to antibiotics and insecticides, is one of the world's biggest medical and public health problems. In a new open access article in Evolutionary Applications, Silvie Huijben and Krijn Paaaijams argue that it is time to put sophisticated evolutionary theory to work to solve the problem.

Huijben, S., & Paaijmans, K. P. (n.d.). Putting evolution in elimination: Winning our ongoing battle with evolving malaria mosquitoes and parasites.

Abstract: Since 2000, the world has made significant progress in reducing malaria morbidity and mortality, and several countries in Africa, South America and South-East Asia are working hard to eliminate the disease. These elimination efforts continue to rely heavily on antimalarial drugs and insecticide-based interventions, which remain the cornerstones of malaria treatment and prevention. However, resistance has emerged against nearly every antimalarial drug and insecticide that is available. In this review we discuss the evolutionary consequences of the way we currently implement antimalarial interventions, which is leading to resistance and may ultimately lead to control failure, but also how evolutionary principles can be applied to extend the lifespan of current and novel interventions. A greater understanding of the general evolutionary principles that are at the core of emerging resistance is urgently needed if we are to develop improved resistance management strategies with the ultimate goal to achieve a malaria-free world.  read more

Evolutionary Applications, n/a-n/a. https://doi.org/10.1111/eva.12530

Evolutionary Toxicology Comes of Age

Evolutionary Toxicology Comes of Age

Evolutionary Applications has a lovely series of articles on Evolutionary Toxicology, now available open access. Highly recommended! 

  1. Evolutionary toxicology: Toward a unified understanding of life's response to toxic chemicals (pages 745–751)Steven P. Brady, Emily Monosson, Cole W. Matson and John W. Bickham
    Version of Record online: 10 NOV 2017 | DOI: 10.1111/eva.12519
  2. Evolutionary toxicology in an omics world (pages 752–761)Elias M. Oziolor, John W. Bickham and Cole W. Matson
    Version of Record online: 20 FEB 2017 | DOI: 10.1111/eva.12462
  3. Elevated mitochondrial genome variation after 50 generations of radiation exposure in a wild rodent (pages 784–791)Robert J. Baker, Benjamin Dickins, Jeffrey K. Wickliffe, Faisal A. A. Khan, Sergey Gaschak, Kateryna D. Makova and Caleb D. Phillips
    Version of Record online: 22 JUN 2017 | DOI: 10.1111/eva.12475
  4. You have full text access to this OnlineOpen articleEvolved pesticide tolerance influences susceptibility to parasites in amphibians(pages 802–812)Jessica Hua, Vanessa P. Wuerthner, Devin K. Jones, Brian Mattes, Rickey D. Cothran, Rick A. Relyea and Jason T. Hoverman
    Version of Record online: 4 JUL 2017 | DOI: 10.1111/eva.12500
  5. You have full text access to this OnlineOpen articleIncorporating evolutionary insights to improve ecotoxicology for freshwater species (pages 829–838)Steven P. Brady, Jonathan L. Richardson and Bethany K. Kunz
    Version of Record online: 10 NOV 2017 | DOI: 10.1111/eva.12507
  6. Adaptation costs to constant and alternating polluted environments (pages 839–851)Morgan Dutilleul, Denis Réale, Benoit Goussen, Catherine Lecomte, Simon Galas and Jean-Marc Bonzom
    Version of Record online: 10 NOV 2017 | DOI: 10.1111/eva.12510
  7. Evolutionary responses to crude oil from the Deepwater Horizon oil spill by the copepod Eurytemora affinis (pages 813–828)Carol Eunmi Lee, Jane Louise Remfert, Taylor Opgenorth, Kristin M. Lee, Elizabeth Stanford, Joseph William Connolly, Jinwoo Kim and Sarah Tomke
    Version of Record online: 16 AUG 2017 | DOI: 10.1111/eva.12502
  8. Genetic and epigenetic variation in Spartina alterniflora following the Deepwater Horizon oil spill (pages 792–801)Marta Robertson, Aaron Schrey, Ashley Shayter, Christina J Moss and Christina Richards
    Version of Record online: 12 MAY 2017 | DOI: 10.1111/eva.12482

Why is natural selection hard to grasp? It is not what you think….

This study of students in a course on evolutionary medicine taught on two separate occasions, found that acceptance is not the problem; human cognitive tendencies interfere more with deep understanding of how natural selection works.  Barnes, M. E., Evans, E. M., Hazel, A., Brownell, S. E., & Nesse, R. M. (2017). Teleological reasoning, not acceptance of evolution, impacts students’ ability to learn natural selection. Evolution: Education and Outreach, 10(1). https://doi.org/10.1186/s12052-017-0070-6  (open access) 

Abstract
Background:  How acceptance of evolution relates to understanding of evolution remains controversial despite decades of research. It even remains unclear whether cultural/attitudinal factors or cognitive factors have a greater impact on student ability to learn evolutionary biology. This study examined the influence of cultural/attitudinal factors (religiosity, acceptance of evolution, and parents’ attitudes towards evolution) and cognitive factors (teleological reasoning and prior understanding of natural selection) on students’ learning of natural selection over a semester- long undergraduate course in evolutionary medicine.
Method:  Pre-post course surveys measured cognitive factors, including teleological reasoning and prior understanding of natural selection, and also cultural/attitudinal factors, including acceptance of evolution, parent attitudes towards evolution, and religiosity. We analyzed how these measures influenced increased understanding of natural selection over the semester.
Results: After controlling for other related variables, parent attitude towards evolution and religiosity predicted students’ acceptance of evolution, but did not predict students’ learning gains of natural selection over the semester. Conversely, lower levels of teleological reasoning predicted learning gains in understanding natural selection over the course, but did not predict students’ acceptance of evolution.
Conclusions:
Acceptance of evolution did not predict students’ ability to learn natural selection over a semester
in an evolutionary medicine course. However, teleological reasoning did impact students’ ability to learn natural
selection.
Signal detection theory illuminates the evolution of immunological systems

Signal detection theory illuminates the evolution of immunological systems

It has long been recognized (at least in evolutionarily informed circles) that the immune system faces a dire tradeoff: too little or too specific a immune response and pathogens triumph, too much or too nonspecific and the system attacks host tissues.  A new paper in Nature Ecology and Evolution analyzes the problem systematically using tools from signal detection theory. This is likely to become a landmark paper. Alas, it is not open access, but the abstract is below.

Metcalf, C. J. E., Tate, A. T., & Graham, A. L. (2017). Demographically framing trade-offs between sensitivity and specificity illuminates selection on immunity. Nature Ecology & Evolution, 1(11), 1766–1772. https://doi.org/10.1038/s41559-017-0315-3

Abstract: A fundamental challenge faced by the immune system is to discriminate contexts meriting activation from contexts in which activation would be harmful. Selection pressures on this ability are likely to be acute: the penalty of mis-identification of pathogens (therefore failure to attack them) is mortality or morbidity linked to infectious disease, which could reduce fitness by reducing lifespan or fertility; the penalty associated with mis-identification of host (therefore self-attack) is immunopathology, whose fitness costs can also be extreme. Here we use classic epidemiological tools to frame this trade-off between sensitivity and specificity of immune activation, exploring implications for evolution of immune discrimination. We capture the expected increase in the evolutionarily optimal sensitivity under higher pathogen mortality risk, and a decrease in sensitivity with increased immunopathology mortality risk; but a number of non-intuitive predictions also emerge. All else being equal, optimal sensitivity decreases with increasing lifespan; and, where sensitivity can vary over age, decreases at late ages not solely attributable to immunosenescence are predicted. These results both enrich and challenge previous predictions concerning the relationship between life expectancy and optimal evolved defenses, highlighting the need to account for epidemiological setting, lifestage-specific immune priorities, and immune discrimination in future investigations.

Sociovirology

Sociovirology

Sociobiology is one thing, but sociovirology? Yes , indeed.  In the realm of viruses it can be tricky to define an individual, and mutation rates are high, but as for all other life, there is kinship and cooperation and competition that can be illuminated by evolutionary principles.

Díaz-Muñoz, S. L., Sanjuán, R., & West, S. (2017). Sociovirology: Conflict, Cooperation, and Communication among Viruses. Cell Host & Microbe, 22(4), 437–441. https://doi.org/10.1016/j.chom.2017.09.012

Virus-virus interactions are pervasive and highly diverse (DaPalma et al., 2010; Figure 1). Some viruses need another, ‘‘helper’’ virus to complete their infection cycle, and other viruses are commonly activated or suppressed by the presence of secondary viral infections. Viral proteins can mix and produce mosaic-like viral particles (pseudotypes) when a cell is coinfected with two different viruses. Viral coinfection of microbes is widespread (Dı´az-Mun˜ oz, 2017), and viruses have mechanisms enabling multiple viral genomes to be cotransmitted in the same infectious unit (reviewed in Sanjua´ n, 2017). Coinfecting viral genomes can be distinct, variants of the same virus, or even genetically identical, suggesting different types of functional interplay. Furthermore, bacteriophages use a form of communication to regulate lysis of the infected cell (Erez et al., 2017). Finally, virus-virus interactions in the absence of cellular coinfection can also be mediated by changes at the host level, such as immune responses. Despite this growing body of empirical evidence suggesting virus-virus interactions, we lack a well-founded conceptual framework that provides an understanding of how these interactions have evolved and how they could shape viral pathogenesis. Social evolution theory was originally developed to explain animal behavior, but has since been extended to microorganisms, including bacteria and unicellular eukaryotes.Yet this social perspective has not been embraced in the study of viruses. read more

Learning objectives for medical education…and how they can improve medical practice

Learning objectives for medical education…and how they can improve medical practice

Bolnick, D. I., Steinel, N., Reynolds, A. W., & Bolnick, D. A. (2017). Learning Objectives for Weaving Evolutionary Thinking into Medical Education. Medical Science Educator, 27(1), 137–145. https://doi.org/10.1007/s40670-017-0375-7  

This new article from the Bolnick group at UT Austin argues describes three learning objectives and three ways they can improve medical practice…IFF they are incorporated into the medical curriculum. 

“We suggest that there are three very general reasons why evolution is relevant to the daily practice of medicine: 1. Understanding the evolutionary origins of genetic diversity within and among human populations helps physicians make appropriate diagnoses and plan treatments. 2. Pathogens and tumors are evolving populations. We must account for their evolution during diagnosis, treatment, and control 3. Evolution provides analytical tools, such as phylogenetics and population genetics, that are used in diagnostics to identify pathogens, trace sources of infection, determine patient ancestry, and interpret genetic markers of disease risk.

We suggest that teaching these ideas in medical school will improve medical practice in three ways. First, understanding evolution can improve diagnosis. For example, familiarity with human evolutionary history and genetic diversity can help physicians avoid racial stereotyping that can lead to misdiagnosis of genetic disorders (case study in box 1). Second, understanding evolution can improve preventative or treatment plans. For example, physicians should have an accurate understanding of natural selection when treating pathogens or tumors that may evolve resistance to drugs (case study in box 2). Third, evolution provides an integrated conceptual framework that helps students learn medical concepts, particularly via comparative anatomy and physiology, and understanding the genetic, environmental, and pathogenic causes of disease.”   p. 138

Abstract Basic science is integral to medical education because it teaches future physicians the fundamental principles of biology they need to become lifelong learners and keep up with expanding medical knowledge. One of these fundamental principles is evolution, which has many practical applications in medicine. Consequently, there is increasing interest in integrating evolutionary biology into medical education. To realize this goal, educators should focus on practical aspects of how knowledge of evolution improves a physician’s ability to prevent, diagnose, and treat disease. This perspective should be woven throughout the curriculum, so evolution comes to be seen as a broadly relevant concept rather than a distinct and peripheral discipline. In particular, we suggest that three general learning objectives be integrated broadly into medical education. First, medical students should be able to apply knowledge of human evolutionary history to explain how genetic variation within and among human populations affects risk, diagnosis, and treatment of disease. Second, students should understand how evolution has led to variation within and between pathogen populations (and tumors), affecting diagnosis and treatment. Third, students should understand how analytical tools from evolutionary genetics are used to determine patient ancestry, disease risk, and pathogen origins. We provide multiple specific topics, case studies, and learning activities within each of these three objectives. The evolutionary medicine learning objectives listed here meet multiple competencies and objectives outlined in the Association of American Medical Colleges (AAMC)/ Howard Hughes Medical Institute (HHMI) 2009 report on the Scientific Foundations for Future Physicians.