Bibliographic record
Abstract
Ecologists and immunologists have long approached scientific inquiry in fundamentally different ways. Immunologists thrive on drilling down into molecular minutiae, but ecologists strive to uncover broad associations between organisms and their environment. One field's signal has also been the other's noise—ecology explores uncontrolled variation, whereas immunology seeks to reduce it at all costs. “When I was in graduate school 10 years ago and I tried to get immunologists to help me, they thought I was crazy,” says Amy Pedersen, a disease ecologist at the University of Edinburgh. But the tides have turned. As lab researchers make forays into immune variation with the microbiome and multiple host infections, they have increasingly sought out Pedersen's ecological expertise. Pedersen is one of a growing number of hybrid researchers—ecologists persuaded by precise tools and immunologists fascinated by variation—who have begun to bridge the two disciplines. So-called ecoimmunologists share the belief that wild animals can help explain disease and immunity in ways that lab mice cannot. Ecoimmunology—sometimes called wild immunology—got its start in October 1982, when William Hamilton and Marlene Zuk published a landmark paper in Science on the links between parasites and sexual selection in passerines, says Lynn Martin, an ecological physiologist at the University of South Florida. On the basis of their data, Hamilton and Zuk concluded that elaborate traits such as colorful plumage may communicate disease resistance to females. Mark Viney, Eleanor Riley, and their team use the popular C57Bl/6 lab strain of Mus musculus in comparison with their wild house mice. Photograph: Stephen Abolins. Over the following decades, ecologists continued to study the immune systems of wild animals—albeit without precise tools. But today, immunologists are joining the effort to understand immune variation, and their research techniques are giving ecoimmunology a much-needed mechanistic boost. Today, much of ecoimmunology focuses on wild rodent systems, which, researchers say, should act as stepping stones between lab mice and humans when developing therapies and vaccines. Take the common house mouse (Mus musculus). According to London lore, half a million rodents scurry over and under the Tube's platforms every day, many of them M. musculus. But these subterranean dwellers differ greatly from their laboratory cousins. Lab mice tend to be “big, fat, lethargic animals” compared with their wild, “lithe” peers, says Mark Viney, a parasitologist at the University of Bristol. Viney and his team are among the first researchers to study M. musculus in the wild. After collecting samples from mice crawling in the London Underground or living on farms around Bristol, the group found that different wild M. musculus individuals exhibit a full spectrum of immune responses—unlike their inbred lab counterparts. But this “shouldn't come as a surprise,” says Viney. Wild mice are “genetically different, they lead different lives, and they're different ages,” much like human populations. The group's unpublished work may redefine what immunologists consider “normal” immune physiology, says Viney. Studies on laboratory mice have found that a particular molecule on the surface of spleen cells is vital to fighting off certain viral infections. But “an awful lot of our wild mice appear to not have that molecule,” he says. “They seem to be what a laboratory mouse immunologist would consider an almost lethal genotype.” These findings imply that “both wild and lab mice can resist these infections, but may do so by completely different mechanisms,” says Eleanor Riley, an immunologist at the London School of Hygiene and Tropical Medicine and Viney's collaborator. “This ‘novel’ mechanism in wild mice may be important in humans as well, but we would not find it by only looking at lab mice.” Viney and Riley see wild M. musculus as an exemplar midway system between the lab mouse and the human—the rodents are easy enough to catch and study in large numbers but variable enough to better model human populations. And given the plethora of studies that lab immunologists have conducted on the species, Viney and Riley also have precise immunological tools at their disposal. “All of the reagents available for lab mice” can also be used in wild M. musculus, explains Jan Bradley, an immunologist at the University of Nottingham. With such reagents, researchers can target specific proteins and cells in a particular species. For example, some reagents measure TH1-type (“helper” cells) but not TH2-type immune cells, which fight virus and worm infections, respectively. In contrast, ecologists have a history of using imprecise measures of immune response, such as skin swelling after an infection of phytohemagglutinin (PHA), a plant-based protein. Viney and Riley's wild rodent system could also have translational value, says Simon Babayan, an immunologist at the University of Glasgow. With the difficulty of translating findings in lab mice to humans in clinical trials, researchers “need a tractable model in which [they] can study the effects of natural variation.” Wild rodents can fill that niche, he says. “You can cure almost anything in a mouse,” says Zoltan Fehervari, an editor at Nature Immunology. But developing vaccines and therapies “becomes a whole lot more complicated” in humans, given our “enormous genetic [and microbiotal] diversity,” he adds. For example, in lab mice, the gene MyD88 codes for a protein that is “essential for innate immune responses,” such that mice with dysfunctional MyD88 can die from the slightest infection, explains Fehervari. “Yet there are [humans] with nonfunctional MyD88 genes who are by and large asymptomatic.” The fact that human immune systems can compensate for such defects suggests that lab-mouse data might not be as generalizable as was previously thought. “It's the big elephant, or big white mouse, in the room,” says Fehervari. Riley emphasizes that different environments can play as important a role in influencing results as genetic variation. “The dirty little secret of immunology is if you take your lovely, clean lab mice from a lab in New York and move them to a lab in San Francisco, all of a sudden, you may start to get different results,” she says. Riley points to the gut microbiome as the likely culprit, because research has shown that it varies with even the slightest change in the environment. Still, top journals, grant-awarding bodies, and drug companies prefer inbred mice studies with dramatic results to research on effects “smeared” by the “complexities” of “other infections or genetic diversity,” says Fehervari. But “we should perhaps all try to re-educate ourselves as editors, referees, and scientists” to welcome subtle discoveries as well, because “that's how biology works.” However, lab co-infection studies are on the rise. For example, a team might investigate the effect of a parasite on virus proliferation in a host—bringing the number of study variables up to two. But when researchers introduce a third factor, the system “goes up orders and orders of magnitude in complexity,” says Fehervari. “Biology [in the wild] is that supercharged.” Fehervari confesses that he has a soft spot for studies that embrace variability and the wild. As a result, he commissioned a 2013 commentary paper on wild immunology with the aim of “testing the waters” with Nature Immunology's audience. Since then, the paper has been cited only 12 times, and many of those were by members of the ecoimmmunology community. Together, ecologists and immunologists are finding ways to investigate complexity in the wild. Pedersen and Babayan, for example, study the interactions of multiple infections in wild wood mice (Apodemus sylvaticus) using transcriptomics and select M. musculus reagents, among other techniques. Unlike reagents, which provide data about particular proteins or cells, transcriptomics produces information on the RNA correlates of a large panel of genes. From these RNA molecules, scientists can infer which proteins are present in the cell. With wood mice, researchers can study a wider range of parasite infections, says Babayan. Wood mice are also found in natural, as opposed to semidomestic, habitats. Therefore, no farmers or London Underground employees are vying for their death. Without the worry of pest control, Pedersen and Babayan can monitor how wood mice immune systems change over time. In a previous study, Pedersen dewormed wild wood mice, released them, and then recaptured the same individuals to measure how other parasites had responded to the treatment. She found that deworming mice led to an increase in other parasitic infections, such as protozoans and cestodes. Her findings, published in Proceedings of the Royal Society B in May 2013, supported the idea that treatment programs using the deworming drug ivermectin may affect host–parasite communities in humans and livestock in unintended ways. “A few years ago, I would have said, sure, everybody recognizes that wild organisms are infected with multiple pathogens and parasites. And yes, we would like to know how all of those [infections] interact—but that's an impossible experiment,” says Brian Lazzaro, a geneticist at Cornell University. But Pedersen is conducting these experiments, and she is “getting good biology out of it,” he adds. Babayan and Pedersen now study wood mice in the lab as well. The lab colony “gives us a level of precision that our wild studies will never be able to reach,” says Pedersen. Lab conditions allow the researchers to control for environmental changes and infection history. By conducting lab co-infection experiments on their genetically diverse wood mice, Babayan and Pedersen can understand baseline immune variation. The researchers have also focused on “getting to know the transcriptome of these animals,” says Babayan. The transcriptome changes with evolving environmental and epidemiological conditions—a technique well suited to wild populations, says Babayan. Transcriptomics also offers a better bang for their buck compared with developing reagents particular to wood mice, he adds. The catch? The researchers have to sort through piles of data to uncover associations relevant to their particular questions. Heligmosomoides polygyrus is a common parasitic worm found in the gut of wood mice and other rodents. Photograph: Simon Babayan. Simon Babayan examines samples from wild wood mice to determine their gastrointestinal diversity. Photograph: Amy Pedersen. Babayan and Pedersen began collaborating in 2009, when Andrea Graham, an immunologist and evolutionary ecologist at Princeton University, realized that her colleagues could fill gaps in each other's research. Babayan had produced a vaccine for filariasis, a worm infection, in the lab but had little experience with testing vaccines under natural conditions. Similarly, Pedersen had studied co-infection in wild populations but had less knowledge of lab immunology. Graham's work also contributes “a perfect piece of the puzzle” to understanding drivers for immune variation, adds Pedersen. In contrast to Pedersen and Babayan's efforts, Graham has begun to study a population of lab mice living in enclosures in the wild. This allows her to “control certain aspects of host genotype and then ask about the role of the environment, for example, in shaping the resistance of hosts against their nematodes,” she says. In October 2010, Graham published a paper in Science that won her—and the field of ecoimmunology—wider recognition. By studying a population of Soay sheep living on St. Kilda, an archipelago off Scotland's coast, Graham and her colleagues showed that an important immune-mediated trade-off may exist between reproduction and survival. In particular, their longitudinal data suggested that sheep with autoimmune phenotypes were more likely to make it through winter and live longer but were less likely to reproduce come spring. “We're used to thinking of autoimmune diseases [such as rheumatoid arthritis] as a negative thing,” says Graham. But “autoimmune prone” individuals may be able to mount potent immune responses, while incurring negligible tissue damage over time. As a result, this condition may be associated with “some benefits, particularly in terms of defense against infection,” she says. Graham's study received attention for its novel outlook on autoimmunity—and its techniques. Unlike many previous ecoimmunological studies, Graham made use of clinical immunological measurements, such as the concentration of antinuclear antibodies (ANAs), or proteins that bind to host cells as if they are foreign. Still, Graham had limited immunological tools compared with those available for wild M. musculus systems, says Riley. By studying a population of Soay sheep living on St. Kilda, an archipelago off Scotland's coast, Andrea Graham and her colleagues showed that an important immune-mediated trade-off may exist between reproduction and survival. Photograph: “Primitive Soay Breed” (http://bit.ly/1RcmQjW) by Philippa Willitts is licensed under CC BY 2.0. Graham is now taking her pioneering work to the next level to ask whether there are similar trends in humans. Specifically, do ANA-positive people—prior to any autoimmune symptoms—experience advantages when confronting infection? And do they live longer as a result? To address her questions, Graham collaborates with researchers who have studied the biology and sociology of aging in human populations. If ANAs are associated with fighting infection and increased life span in humans, Graham would like to work out the mechanisms behind this phenomenon. “ANAs are a heterogeneous population” of antibodies, she explains. That is, some subtypes of ANAs may display nonspecific, or innate, immune defenses such as tissue repair, whereas others may attack specific cells. One study might disentangle such complexity by sorting the different ANA types, transferring those subsets into different groups of lab mice and tracking the consequences of those infusions over time. “What I'm proposing is to have the best of both worlds—to use the very reductionist aspects of mouse immunology but also to study life span, which is not something most people studying mice do,” says Graham. “It would be pretty hard—I think that's why nobody has done it yet.” But perhaps if she finds the same connection in humans, this would convince her more mechanism-oriented colleagues—and grant-awarding bodies—of this endeavor's worthiness. After the 2010 sheep study, Graham says she came to a “crossroads,” with one path leading to “delving deeper into mechanisms” and another to investigating human populations. With a background in population biology, Graham chose the latter road. But her ability to develop and collaborate on mechanistic studies has not gone unnoticed. Martin, of the University of South Florida, describes Graham as a “hub” for ecologists and immunologists because she can “speak both languages,” much like Pedersen. But being a hybrid scientist can also lead to questions of scientific identity. Andrea Graham and her PhD student Jacqueline Leung weigh house mice that live in seminatural enclosures. Photograph: David Tricker. Back in the late 1990s, University of Nottingham's Bradley began her own trek to the midpoint between ecology and immunology. While investigating mechanisms for human immunity to river blindness, a disease caused by a parasitic worm, she grew “cynical” about attributing the cause of the ailment to particular immunological pathways. Bradley wondered whether the distance individuals live from the river, where flies that carry the parasite breed, might affect chances of infection. She also became curious about how protective clothing could influence an individual's risks. In order to fully understand immunity to a disease, “you need to account for all of those variables, and that's ecology, isn't it?” says Bradley. “I'm realizing that I've been trying to be an ecologist for all my life in a way.” Today, Bradley participates in a collaboration in which both her ecological outlook and her immunological training can be put to good use. Bradley and her colleagues at the University of Liverpool assess as many parameters as they can—genetic, environmental, or otherwise—to pinpoint the drivers of strategies against disease. To accomplish this task, the group has jumped on the network theory bandwagon, an analysis technique that has found its way into nearly all disciplines of science—from physics to sociology. Network analysis simply says that if two or more variables are very close together in a web of variables, then they most likely work together to bring about a certain trait or response. In terms of physiology, proximity in a web would suggest that variables contribute to the same regulatory pathway. Steve Paterson, a geneticist at Liverpool and the network project's principal investigator, that immunologists have used network analysis to molecular in the But his team may be the first to and environmental data in a network with the aim of the drivers behind different immune strategies in the wild. network analysis can be used to both uncover mechanistic and address variation, the bridge the between lab and wild he adds. To their analysis the team also from experience with the group's study an ecologist at has studied a wild population living Liverpool chose the in because these wood to lab mice. 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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.013 |
| Insufficient payload (model declined to judge) | 0.060 | 0.017 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".