A Rambaut

A. C McHardy

B. L Haagmans

Catriona J. MacCallum

D Butler

D Falush

D Koppstein

E. C Berglund

E. C Holmes

G. J. D Smith

I Comas

I Evans

J Coloma

Jonathan A. Eisen

K. L Seib

L Allen

M. S Dorer

P. J Brindley

R Gupta

S Porter

W. C Van Voorhis

W. F Fricke

PLoS Biology

English

PubMed

Jonathan A Eisen

Catriona J MacCallum

Directory of Open Access Journals

Genomics of emerging infectious disease: A PLoS collection.

Eisen, Jonathan A

MacCallum, Catriona J

eScholarship - University of California

UC DavisUC Davis Previously Published WorksTitleGenomics of emerging infectious disease: A PLoS collection.Permalinkhttps://escholarship.org/uc/item/63t5j5r0JournalPLoS biology, 7(10)ISSN1545-7885AuthorsEisen, Jonathan AMacCallum, Catriona JPublication Date2009-10-01 Peer reviewedeScholarship.org Powered by the California Digital LibraryUniversity of CaliforniaEditorialGenomics of Emerging Infectious Disease: A PLoSCollectionJonathan A. Eisen1*, Catriona J. MacCallum2*1 University of California Davis, Davis, California, United States of America, 2 Public Library of Science, Cambridge, United KingdomToday, the Public Library of Science publishes a collection ofessays, perspectives, and reviews about how genomics, with all itsassociated tools and techniques, can provide insights into ourunderstanding of emerging infectious disease (http://ploscollections.org/emerginginfectiousdisease/) [1–13]. This collection, focused onhuman disease, is particularly timely as pandemic H1N1 2009influenza (commonly referred to as swine flu) spreads around theglobe, and government officials, the public, journalists, bloggers, andtweeters strive to find out more. People want to know if this flu posesmore of a threat than other seasonal flu strains, how fast it’sspreading (and where), and what can be done to contain it. As thiscollection illustrates, the increasing speed at which complete genomesequences and other genome-scale data can be generated forindividual isolates and strains of a pathogen provides tremendousopportunities to identify the molecular changes in these diseaseagents that will enable us to track their spread and evolution throughtime (e.g., [3,7,8]) and generate the vaccines and drugs necessary tocombat them (e.g., [5–7]). The collection also shines a spotlight onspecific pathogens, some familiar and widespread, such as theinfluenza A virus (e.g., [9]); some ‘‘reemerging,’’ such as theMycobacterium tuberculosis complex that causes tuberculosis [10]; andsome identified only recently, as with the bacterium Helicobacter pylori(which causes peptic ulcers and gastric cancer [11]).There is no simple definition of an emerging disease, but it canbe loosely described as a disease that is novel in some way—forexample, one that displays a change in geographic location,genetics, or function. Emerging infectious diseases are caused by awide range of organisms, but they are perhaps best typified byzoonotic viral diseases that cross from animal to human hosts andcan have a devastating impact on human health, causing a highdisease burden and mortality [8]. These zoonotic diseases includemonkeypox, Hendra virus, Nipah virus, and severe acuterespiratory syndrome coronavirus (SARS-CoV), in addition toinfluenza A and the lentiviruses that cause AIDS. The apparentlyincreased transmission of pathogens from animals to humans overthe recent decades has been attributed to the unintendedconsequences of globalization as well as environmental factorsand changes in agricultural practices [8]. Generally, the burden ofthese diseases is most strongly felt by those in developing countries.Brindley et al. [12] point to the debilitating effects of the mostcommon human infectious agent in such areas—helminths(parasitic worms)—and the role that genomics plays in advancingour understanding of molecular and medical helminthology.Compounding the problem of emerging infectious diseases indeveloping countries is the reality that researchers in developingcountries have often been unable to participate fully in genomicsresearch, because of their technological isolation and limitedresources. As Harris et al. emphasize [13], ‘‘collaborations—starting with capacity building in genomics research—need to befostered so that countries that are currently excluded from thegenomics revolution find an entry point for participation.’’This collection is a collaborative effort that combines financialsupport from Google.org (which has also sponsored research onemerging infectious disease through its Predict and Preventinitiative [14]) with PLoS’s editorial independence and rigor.Gupta et al. [1] provide Google.org’s perspective and vision forhow systematic application of genomics, proteomics, and bioinfor-matics to infectious diseases could predict and prevent the nextpandemic. To realize this vision, they urge the community to uniteunder an ‘‘Infectious Disease Genomics Project,’’ analogous to theHuman Genome Project. This is, as the authors admit, apotentially ‘‘grandiose’’ and difficult proposition. Some researchersmight justifiably argue that much is already being achieved—asdemonstrated by this collection—and that the vision is naı̈ve.However, as every article in the collection also points out,tremendous challenges remain if the potential of genomics in thisfield is to be realized.One problem is that, despite the fact that sequencing is now themethod of choice for characterizing new disease agents, and newsubstantially faster and cheaper sequencing methods are contin-ually being produced, we still lack the range of computational toolsnecessary to analyze these sequences in sufficient detail [4]. It ispossible to sequence the entire assemblage of viruses in a particulartissue type or host species [3] and to obtain complete or nearlycomplete genome sequences for large samples of bacteria [7]. Yetwe remain in the early, albeit essential, stages of pathogendiscovery (Box 1). These sequences can be interpreted fully onlywhen integrated with relevant environmental, epidemiological,and clinical data (e.g., [3,4,8]). And, despite the increasedsequencing, really comprehensive genome data are still onlyavailable for a few key pathogens, which further limits ourunderstanding. For example, a full quantitative understanding ofthe processes that shape the epidemiology and evolution—thephylodynamics—of RNA viruses is currently possible only for HIVand influenza A virus [3].In this collection, you will find not only the views of leadingresearchers from several different disciplines, and a provocativevision from a funding agency, but also the contributions of sixdifferent PLoS journals (PLoS Biology, PLoS Medicine, PLoSComputational Biology, PLoS Genetics, PLoS Neglected Tropical Diseases,and PLoS Pathogens). The PLoS open-access model of publishingmakes possible such a large multidisciplinary cross-journalcollection, in which all articles are simultaneously available onlineCitation: Eisen J, MacCallum CJ (2009) Genomics of Emerging Infectious Disease:A PLoS Collection. PLoS Biol 7(10): e1000224. doi:10.1371/journal.pbio.1000224Published October 26, 2009Copyright:  2009 Eisen, MacCallum. This is an open-access article distributedunder the terms of the Creative Commons Attribution License, which permitsunrestricted use, distribution, and reproduction in any medium, provided theoriginal author and source are credited.Competing Interests: The authors have declared that no competing interestsexist.* E-mail: jaeisen@ucdavis.edu (JAE); cmaccallum@plos.org (CJM)This article is part of the ‘‘Genomics of Emerging Infectious Disease’’ PLoS Journalcollection (http://ploscollections.org/emerginginfectiousdisease/).PLoS Biology | www.plosbiology.org 1 October 2009 | Volume 7 | Issue 10 | e1000224for unrestricted reuse, regardless of venue (see also the podcast thataccompanies the collection; http://ploscollections.org/ /emerginginfectiousdisease.mp3).Our aim is that this collection will add to other ‘‘open science’’activities that have helped provide insights into infectious diseasemore quickly than would have been thought feasible only a fewyears ago. This accelerated availability of research findings isexemplified by the recent response to the flu pandemic. Consider,for example, data access. Traditionally, scientists have releaseddata after publishing a study. Fortunately, in part due toexperience from genome sequencing projects, prepublication flusequence data have been released in a relatively unrestrictedmanner to the community [15]. This has in turn enabledanyone—not just those who collected the data—to carry outanalyses while the epidemic is occurring (when in principle there isstill time to save lives) rather than being forced to provide aBox 1. A Field Guide to Microbes?When an American robin (Turdus migratorius) showed up in London a few years ago, birders were rapidly all atwitter and manycame flocking to town [22]. Why had this one bird created such a stir? For one main reason—it was out of place. This species isnormally found in North America and only very rarely shows up on the other side of the ‘‘pond.’’ Amazingly, this rapid, collectiveresponse is not that unusual in the world of birding. When a bird is out of place, people notice quickly.This story of the errant robin gets to the heart of the subject of this collection because being out of place in a metaphorical wayis what defines an emerging infectious disease. Sometimes we have never seen anything quite like the organism or the diseasebefore (e.g., SARS, Legionella). Or perhaps, as with many opportunistic pathogens, we have seen the organism before but it wasnot previously known to cause disease. In other cases, such as with as pandemic H1N1 2009 or E. coli O157:H7, we have seenthe organism cause disease before but a new form is causing far more trouble. And of course organisms can be literally out ofplace, by showing up in a location not expected (e.g., consider the anthrax letters [2]).Historically, despite the metaphorical similarities with the robin case, the response to emerging infectious disease is almostalways much slower. Clearly, there are many reasons for these differences, which we believe are instructive to consider. At leastfour factors are required for birders’ rapid responses to the arrival of a vagrant bird: (1) knowledge of the natural ‘‘fauna’’ in aparticular place, (2) recognition that a specific bird may be out of place, (3) positive identification of the possibly out-of-placebird, and (4) examination of the ‘‘normal’’ place for relatives of the identified bird.How are these requirements achieved? Mostly through the existence of high-quality field guides that allow one to place anorganism such as a bird into the context of what is known about its relatives. This placement in turn is possible because of twokey components of field guides. First, such guides contain information about the biological diversity of a group of organisms.This usually includes features such as a taxonomically organized list of species with details for each species on biogeography(distribution patterns across space and time, niche preferences, relative abundance), biological properties (e.g., behavior, size,shape, etc.), and genetic variation within the species (e.g., presence of subspecies). Second, a good field guide providesinformation on how to identify particular types (e.g., species) of those organisms. With such information, and with a network ofinterested observers, an out-of-place bird can be detected with relative ease.In much the same way, a field guide to microbes would be valuable in the study of emerging infectious diseases. The articles inthis collection describe what can be considered the beginnings of species-specific field guides for the microbial agents ofemerging diseases. If we want to truly gain the benefits that can come from good field guides it will be necessary to expandcurrent efforts to include more organisms, more systematic biogeographical sampling, and more epidemiological and clinicaldata. But the current efforts are a great start.Figure: The American Robin (Turdus migratorius). (Photo Credit: NASA).doi:10.1371/journal.pbio.1000224.g001PLoS Biology | www.plosbiology.org 2 October 2009 | Volume 7 | Issue 10 | e1000224downloadsposthumous account of the spread of infection. Such a responsehighlights both the importance of early data access and theremoval of restrictions in the use of data (e.g., in many past casesdata might be released but use of the data in presentations andpublications would be limited).The value of open access to sequence data is helping to putpressure both on private organizations to release their sequencedata [16,17] and on all agencies to release other information (e.g.,metadata about strains) more rapidly. This pressure is not beingbrought to bear only on flu data—in this collection Van Voorhiset al. [5] call on pharmaceutical companies to deposit thestructural coordinates of drug targets from all globally importantinfectious disease organisms in public databases.Of course, data about any infectious disease are not very usefulunless placed in the scientific context of past studies (i.e.,publications) specifically about the disease or about methods toanalyze such data. It is also important to have access toinformation about other diseases and other organisms that mightimpact its spread or evolution. Perhaps the most intriguing aspectof open science in response to flu has been the move toward pre-journal publication release of findings. Many flu researchers tookthe available data, analyzed it, and posted results on blogs [18,19],wikis [20], and other sites. Although some view this ‘‘non peer-reviewed’’ release as unseemly, it is clear that it has helpedaccelerate the science in the study of pandemic H1N1 2009 andled to some important journal papers [17]. Indeed, such advanceshelped provide one of the stimuli for PLoS’s most recent initiative,PLoS Currents: Influenza, a Google ‘‘Knol,’’ for the rapidcommunication of research results and ideas about flu vetted byexpert moderators [21].This is not to say there are no possible risks or drawbacks frommore openness. For example, some governments may avoidreleasing data because of fears about discrimination (as was seen inmany aspects of the flu in Mexico). Others worry that completeopenness might foster the spread of misinformation. However, asFricke et al. argue in their article on the relationship betweengenomics and biopreparedness [2], open source genomic resourcesare actually of immense benefit to those in charge of our publichealth and biosecurity.It is clear that ‘‘for all stages of combating emerging infections,from the early identification of the pathogen to the developmentand design of vaccines, application of sophisticated genomics toolsis fundamental to success’’ [8]. It is equally clear that open scienceand open access to publications and data will be key to thatsuccess. Whatever one’s position has been on the various openscience initiatives, there is no doubt that the ‘‘esoteric’’ label onsome open science initiatives has largely been eliminated by theemergence of H1N1 flu epidemic.The faster, cheaper, and more openly we can distribute thediscoveries of science, the better for scientific progress and publichealth. As this collection emphasizes, managing the threat ofnovel, re-emerging, and longstanding infectious diseases ischallenging enough even without barriers to scientific research.We encourage you to make the most of this collection by sharing,rating, and annotating the articles using our online commentingtools. Better yet, join the discussion by providing your own visionto prevent the emergence and spread of the next rogue pathogen.References1. Gupta R, Michalski MH, Rijsberman FR (2009) Can an Infectious DiseasesGenomics Project predict and prevent the next pandemic? PLoS Biol 7:e1000219. doi:10.1371/journal.pbio.1000219.2. Fricke WF, Rasko DA, Ravel J (2009) The role of genomics in the identification,prediction, and prevention of biological threats. PLoS Biol e1000217. doi:10.1371/journal.pbio.1000217.3. Holmes EC, Grenfell BT (2009) Discovering the phylodynamics of RNA viruses.PLoS Comput Biol 5: e1000505. doi:10.1371/journal.pcbi.1000505.4. Berglund EC, Nystedt B, Andersson SGE (2009) Computational resources ininfectious disease: Limitations and challenges. PLoS Comput Biol 5: e1000481.doi:10.1371/journal.pcbi.1000481.5. Van Voorhis WC, Hol WGJ, Myler PJ, Stewart LJ (2009) The role of medicalstructural genomics in discovering new drugs for infectious diseases. PLoS CompBiol 5: e1000530. doi:10.1371/journal.pcbi.1000530.6. Seib KL, Dougan G, Rappuoli R (2009) The key role of genomics in modernvaccine and drug design for emerging infectious diseases. PLoS Genet 5:e1000612. doi:10.1371/journal.pgen.1000612.7. Falush D (2009) Toward the use of genomics to study microevolutionary changein bacteria. PLoS Genet 5: e1000627. doi:10.1371/journal.pgen.1000627.8. Haagmans BL, Andeweg AC, Osterhaus ADME (2009) The application ofgenomics to emerging zoonotic viral diseases. PLoS Pathog 5: e1000557.doi:10.1371/journal.ppat.1000557.9. McHardy AC, Adams B (2009) The role of genomics in tracking the evolution ofinfluenza A virus. PLoS Pathog 5: e1000566. doi:10.1371/journal.ppat.1000566.10. Comas I, Gagneux S (2009) The past and future of tuberculosis research. PLoSPathog 5: e1000600. doi:10.1371/journal.ppat.1000600.11. Dorer MS, Talarico S, Salama NR (2009) Helicobacter pylori’s unconventionalrole in health and disease. PLoS Pathog 5: e1000544. doi:10.1371/journal.ppat.1000544.12. Brindley PJ, Mitreva M, Ghedin E, Lustigman S (2009) Helminth genomics:The implications for human health. PLoS Negl Trop Dis 3: e538. doi:10.1371/journal.ppat.1000538.13. Coloma J, Harris E (2009) Molecular genomic approaches to infectious diseasesin resource-limited settings. PLoS Med 6: e1000142. doi:10.1371/journal.pmed.1000142.14. Google.org (2008) Predict and Prevent Initiative homepage. Available: http://www.google.org/predict.html. Accessed 16 September 2009.15. National Center for Biotechnology Information (2009) Influenza VirusResource. Available: http://www.ncbi.nlm.nih.gov/genomes/FLU/SwineFlu.html. Accessed 11 September 2009.16. Butler D (2005) Flu researchers slam US agency for hoarding data. Nature 437:458–459.17. Smith GJD, Vijaykrishna D, Bahl J, Lycett SJ, Worobey M, et al. (2009) Originsand evolutionary genomics of the 2009 swine-origin H1N1 influenza Aepidemic. Nature 459: 1122–1125.18. Porter S (2009) Did the California H1N1 swine flu come from Ohio?Discovering Biology in a Digital World blog. Available: http://scienceblogs.com/digitalbio/2009/04/did_the_california_h1n1_swine.php. Accessed 11September 2009.19. Koppstein D (2009) Swine flu phylogeny, part II. Koppology blog. Available:http://koppology.blogspot.com/2009/04/swine-flu-phylogeny-part-ii.html. Ac-cessed 11 September 2009.20. Rambaut A (2009) Human/Swine A/H1N1 Influenza Origins and Evolution.Available: http://tree.bio.ed.ac.uk/groups/influenza/. Accessed 11 September2009.21. Allen L (2009) Welcome to PLoS Currents: Influenza. PLoS Blog. Available:http://www.plos.org/cms/node/481. Accessed 8 September 2009.22. Evans I (29 March 2009) American Robin Spotted in South London.Foxnews.com. Available at:http://www.foxnews.com/story/0,2933,189510,00.html. Accessed 14 September 2009.PLoS Biology | www.plosbiology.org 3 October 2009 | Volume 7 | Issue 10 | e1000224

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Genomics of Emerging Infectious Disease: A PLoS Collection

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