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Parasite microbiome project: Grand challenges

The first Parasite Microbiome Project (PMP) Workshop (January 9–14, 2019, Clearwater, Florida, United States) hosted researchers from across continents and disciplines to lay the foundation of the PMP consortium. The PMP vision is to catalyze scientific discourse and explorations through a systems approach, toward an integrated understanding of the microbiota of parasites and their impact on health and disease. The participants identified knowledge gaps and grand challenges in the field of host–parasite–microbe interactions summarized here. The PMP will provide an interactive centralized platform and resource for transdisciplinary collaboration to propel the field of parasitology forward by disentangling complex interactions between parasites and hosts, their respective microbiota, and microbial communities in the parasite’s direct environment (Fig 1).

Fig 1. The complex nature and interrelations of host–parasite–microbe interactions are illustrated using a Matryoshka (Russian nesting) doll metaphor.

The PMP aims to elucidate nested interactions between a given host and parasites (e.g., helminths and protists) that are themselves hosts to their own symbionts and parasites (e.g., viruses and bacteria). Artwork by Meredith Brindley ( PMP, Parasite Microbiome Project.

Parasitism is a successful lifestyle that has evolved in virtually every clade of multicellular organisms [13] and protists [4, 5]. Parasitology seeks to develop the means to prevent, limit, or cure infections by parasites for the benefit of humans, agriculture, and wildlife and to understand how parasitism and parasitic disease impact not only the host but also host communities and ecosystem health. This is a challenging task, considering the diversity and complex nature of host–parasite interactions. Parasitic organisms harbor a rich tapestry of traits associated with survival and must navigate the host immune response to reproduce and be effectively transmitted to the next host.

An improved understanding of underlying molecular mechanisms and evolutionary patterns that explain interindividual, temporal, and geographic variation in the outcomes of parasitic infections is much needed [69]. There is an increasing recognition of the potential for host- and parasite-associated microbiota―endo- and/or ectosymbiotic archaea, bacteria, viruses, and micro-eukaryotes―to influence and shape host–parasite interactions [10]. In the past few years, the concept of individuality has given way to that of “holobiont” with the recognition that each organism is a composite of organisms [1114] (Fig 1, Box 1). Yet we have limited insight into the nature and importance of these interactions for parasite ecology and evolution [15, 16], and not a single parasite species has its entire microbiome fully characterized.

Box 1. Key microbiome and holobiont concepts applied to parasitology

Direct environment: environment of the parasite at the time of sampling (host-associated and free-living stages).

Parasite-associated microbiome: collection of the genomes of the microbiota (viruses, bacteria, archaea, and micro-eukaryotes) that are either chromosomally integrated or episomal, intracellular, or attached to the surface of the parasite.

Host-associated microbiome: collection of the genomes of the microbiota that are associated with the host, either in the direct environment of the parasite, or in a distant tissue or anatomic compartment of the host.

Environmental microbiome: collection of the genomes of the microbiota that are present in the direct environment of free-living (encysted or mobile) life stages of parasites.

Holobiont: a unit of biological organization composed of a host and its microbiota, inclusive of transient and persistent microbes.

Hologenome: the complete genetic content of an organism’s genome, including nuclear and organellar genomes, and its microbiome.


The PMP envisions a holistic understanding of host–parasite–microbe interactions by fostering global transdisciplinary explorations of the microbiomes of parasites and their direct environment (Fig 2; Box 1) [17]. The PMP will be enabled by new and existing tools, technologies, and standards developed for microbiomes and tailored for analyses of host–parasite–microbe interactions. Areas of focus will include (1) development of relevant standards for metadata collection and curation, (2) methods development for processing of parasite-associated microbes, (3) multi-omics technologies, and (4) tailoring of analytical tools for parasite-associated microbiome research. Methods and data will be shared freely with the scientific community and public using open data standards. Establishing and optimizing these methods will initially require a “test” collection of well-characterized parasite isolates/models and a comprehensive identification of parasite-associated microbes. The PMP will establish a workflow and centralized platform to maximize parasite sampling efforts and facilitate parasite microbiome research for the community at large (Fig 3; Table 1).

Fig 2. Examples conveying context-dependent usage of the microbiome and holobiont concepts in parasitology.

(A) Procercoid stage of the cestode Schistocephalus solidus in the body cavity of a cyclopoid copepod. The Pam may be collected from procercoids. The De is the body cavity of the copepod. The Ham may be collected from the gut or other host tissues whereas the Em may be collected from the water. (B) Oocyst of Toxoplasma gondii that sporulated upon excretion with cat feces. The Pam may be collected from purified oocysts. Distinction between the Ham, De, and Em is difficult. (C) Trypanosoma sp. among red blood cells. The Em is not represented. The intracellular microbes potentially present within red blood cells may be considered Ham whereas microbes within the plasma can be considered in the De of the parasite. Image credits: M. Hahn; L. Knoll and J. P. Dubey; J. Lukeš. De, direct environment; Em, environmental microbiome; Ham, host-associated microbiome; Pam, parasite-associated microbiome.

Fig 3. Proposed workflow for processing PMP samples from parasites and host tissues.

PMP, Parasite Microbiome Project.

Table 1. Methods to tackle the grand challenges of parasite microbiome research.

A primary advantage of a centralized platform like the PMP is the collation of large aggregates of associated metadata that can be harnessed to uncover, and eventually understand, patterns of microbial diversity and ecology [40, 35]. Therefore, detailed metadata associated with each study and sample are absolutely critical to maximize the utility of each. To facilitate future research opportunities, the PMP will encourage tracking of metadata connected to both the sample and its processing and the deposition of host and parasite vouchers into museum collections to allow future analysis opportunities when new techniques and hypotheses arise [41, 42]. Any additional tissues and extracted biomolecules should also be maintained in dedicated (cryo-) collections. We will adapt practices and lessons learned by the Earth Microbiome Project (EMP) [35, 43], e.g., preparation of multiple (homogenous) aliquots of the samples to be studied [44], in a manner that is best suited for the PMP. By providing tested methods and developing standards for parasite microbiome research, the PMP foresees the following:

  • Elevating the integral role of the microbiome in host–parasite ecology and evolution (in a dynamic environment) to promote solution-oriented research in parasitic disease management.
  • Steering the larger microbiome community towards analysis of the micro-eukaryotic component of the microbiome.
  • Building an inclusive and transdisciplinary PMP community that catalyzes analysis of natural and model parasite systems.
  • Becoming a community hub that coordinates discussions fostering collaborative research to address current and future grand challenges.

Grand challenges

We encourage the scientific community to join the PMP in addressing grand challenges in the field of host–parasite–microbe interactions and designing creative experiments in a diversity of systems to explore the areas outlined next.

Identifying core and transient parasite-associated microbes

Parasite-associated microbiomes remain largely unknown, in part due to the inherent difficulties of studying the parasites themselves, e.g., challenging or nonexistent in vitro cultivation systems, complex life cycles, ethical considerations, obligate host environments that are difficult to simulate in experimental models, and national borders. Another specific challenge for investigating microbial communities associated with parasites is the necessity to isolate the parasite from the background sampled material and from host-associated microbes. The microbiota within a parasite can be divided into core microbes (intrinsic to the parasite or at least to a specific parasitic life stage) and transient microbes (temporarily acquired by the parasite from its direct environment). Comparative analyses between the parasite microbiome, the microbiome of the corresponding infected host, and a control noninfected host from the same environment will be needed to rule out potential microbial contaminants from the direct environment.

Parasite holobiont research will need to ascertain whether microbes are vertically transmitted from parasitic parent to offspring, horizontally transmitted between parasites coinfecting the same host, or transmitted between the parasite and its direct environment (the host or the external environment of the free-living stages). The objective will be to discern to what extent the parasite-associated microbiota is determined by the parasite (maintained across developmental growth, reproduction, and dispersal), by the composition of the microbiota in its direct environment, or by abiotic factors. This objective could be examined, for example, by comparing the microbiomes of parasites (1) infecting multiple host species (for generalist parasites or parasites with complex life cycles), (2) at different life stages, (3) isolated from spatially and temporally separated populations or populations with different diets, or (4) coinfecting the same host.

Understanding the roles of parasites in microbe evolution and host–microbe interactions

Parasite prevalence in a population, route(s) of parasite transmission, and interdependence between the microbe and its parasitic host will drive the evolution of the microbe’s modes of transmission. These modes are of particular interest because they will drive microbial virulence both for the parasite and its host [45]. Parasites may influence the composition of the microbiota of their hosts by diverse means. For example, parasites may (1) be vectors or reservoirs of microbes; (2) exert pressure on the host during infection, leading to the evolution of defensive microbes; (3) compete with host microbiota for nutrients or provide metabolic and genetic reservoirs to support the growth and survival of other host microbial species; (4) modify the host environment, e.g., pH, to the benefit of other microbes; and/or (5) induce an immune response by the host that, in turn, impacts the host’s microbiome.

The extent to which the host microbiome is determined by its parasites can be investigated by comparing the microbiome of individuals infected by different parasitic species and/or strains [46]. When treatments are available, they can be used to determine whether the host microbiome returns to its original state after removal of the parasite. In addition, characterizing the underlying mechanisms will be necessary to determine whether the parasite directly or indirectly interacts with the host microbiome and whether this is beneficial to the parasite or a side effect of the infection. Furthermore, by serving as vectors or reservoirs of microbes, parasites could alter the evolution of microbes by providing opportunities for host switching or novel microbe–microbe interactions that may lead to genetic exchanges. In order to gain an evolutionary perspective on host–parasite–microbe interactions, evolutionary studies encompassing microbes across host and parasite species are necessary to identify patterns of cospeciation and speciation following host shifts.

Understanding the functional role of microbes in parasite fitness and host diseases

Parasites and associated microbes can be viewed as a community of organisms that experience different selection pressures, despite the high potential for interdependence. Microbes can be either beneficial (mutualistic) or antagonistic (parasitic or with fitness conflicts) to the parasite. The nature of the interaction would lead to radically different effects of the microbes on the evolution of the holobiont and the host–parasite interaction. Similarly, microbes associated with the host may be beneficial for the parasite, as a result of selection for cooperation, or they may be detrimental due to the competition for nutrients and/or space. The nature of parasite–microbe interactions may have a critical effect on the parasite’s fitness and host disease. For example, viral symbionts of parasitic protists can divert host responses toward antiviral immunity, which is inefficient in clearing the eukaryotic infection and may aid the parasite survival [21].

Understanding the impact of microbes on the fitness of hosts and parasites is of relevance to epidemiological studies and is expected to provide new opportunities for therapeutic interventions. The inherent complexity of the study of host–parasite–microbe interactions necessitates the application of methods from the field of community genetics, wherein it is acceptable that the gene that governs a given phenotype resides in the genome of another species and is dependent on the environment [47]. Here, the environment of the host and parasite is the microbiome, and its impact on the evolution of the system can be tested by measuring parameters of the host and parasite fitness in the presence of different microbes. Alternatively, host–microbe interactions can be tested by considering the host as the environment.

Identifying patterns and processes of host–parasite–microbe coevolution

Interindividual variations in the outcome of a parasitic infection resulting from variations in host susceptibility, parasite virulence, and host–parasite compatibility can be better understood in the context of the geographic mosaic of coevolution [48]. Microbes also show geographic variation, and they can participate in coevolution by shifting selection pressures away from or towards either the host or the parasite [4951]. With appropriate experimental systems, geographic variations affecting the role of microbes in host–parasite interactions can be assessed by using a complete cross-experimental design, in which hosts from different localities are infected with parasites from their corresponding localities in the presence of either microbes isolated from the same localities or microbes from different test localities. Identification of temporal variations in selection pressures on microbes involved in host–parasite interactions would require time-shift experiments, wherein the microbes that have evolved with the host and parasite are transferred back to an ancestral host and parasite. Finally, when possible, experimental evolution of parasites and hosts in the presence or absence of the identified microbes can been used to test the effect of specific microbes on the evolution of the system and to identify mechanisms involved in parasite–microbe interaction.

Moving forward

The PMP consortium proposes a two-phase development, analogous to the Human Microbiome Project (HMP) [52]. Phase one will compile information on previously characterized parasite-associated microbes and parasite–microbe interactions (already partially reviewed in [1516, 53]), mine genomic and transcriptomic databases to detect microbial sequences, and characterize the complete microbiome of a set of parasites representing diverse taxa and environments. A main focus during this phase will be on preparing a website and developing and sharing best practices, methods, and standards for effective sample management and integration of data. The PMP, in collaboration with the Genomic Standards Consortium (GSC;, has initiated the development of a new parasite-associated package to be added to the Minimal Information about any Sequence (MIxS) standard [18]. This package will facilitate the collection, standardization, reporting, and integrated analyses of metadata to capture the parasite microbiome contextual information describing the host, environment, sample and sequencing data. We anticipate the MIxS-PMP to be available by the end of 2019.

The second phase of the project will rely on the development of experimental model systems that may be employed to prove cause-effect relationships between parasite virulence, diseases, and microbiome composition, as well as to investigate the underlying molecular mechanisms and the evolution of host–parasite–microbe interactions. Findings from initial microbiome characterizations during phase one and previously proposed experimental model systems [53] will guide the evaluation and selection of systems most suitable for addressing the scientific grand challenges identified herein.

Given the important role of parasites in ecosystems, human health, and agricultural management, propelling the field of parasitology in a coordinated way with the PMP can have an enormous payoff (Table 2). The PMP will necessitate both significant funding to conduct challenging research as well as engagement from the community to provide high-quality samples and to share detailed and accurate metadata information. Therefore, we propose constituting a community of researchers that meet annually for workshops and symposia. With this opinion article, we invite reader comments to better define grand challenges and research needs moving forward.

Table 2. Representative examples of organisms for which uncovering parasite–microbe interactions is allowing major scientific advances.

It is anticipated that the PMP will advance the field by facilitating similar research on diverse parasites and uncover patterns of microbial diversity and ecology that apply across phyla.


The authors thank Jack Gilbert for his assistance and comments to this initiative and Meredith E. Brindley for assistance with the scientific illustration.


  1. 1. Weinstein SB, Kuris AM. Independent origins of parasitism in Animalia. Biol Lett. 2016;12: 20160324. pmid:27436119
  2. 2. Westwood JH, Yoder JI, Timko MP, dePamphilis CW. The evolution of parasitism in plants. Trends Plant Sci. 2010;15: 227–235. pmid:20153240
  3. 3. Poulin R, Morand S. The diversity of parasites. Q Rev Biol. 2000;75: 277–293. pmid:11008700
  4. 4. Baker JR. The origins of parasitism in the protists. Int J Parasitol. 1994;24: 1131–1137. pmid:7729973
  5. 5. Adl SM, Bass D, Lane CE, Lukeš J, Schoch CL, Smirnov A, et al. Revisions to the classification, nomenclature, and diversity of eukaryotes. J Eukaryot Microbiol. 2019;66: 4–119. pmid:30257078
  6. 6. Dybdahl MF, Jenkins CE, Nuismer SL. Identifying the molecular basis of host-parasite coevolution: merging models and mechanisms. Am Nat. 2014;184: 1–13. pmid:24921596
  7. 7. Pulgarín-R PC, Gómez JP, Robinson S, Ricklefs RE, Cadena CD. Host species, and not environment, predicts variation in blood parasite prevalence, distribution, and diversity along a humidity gradient in northern South America. Ecol Evol. 2018;8: 3800–3814. pmid:29721258
  8. 8. Cable J, Barber I, Boag B, Ellison AR, Morgan ER, Murray K, et al. Global change, parasite transmission and disease control: lessons from ecology. Philos Trans R Soc Lond B Biol Sci. 2017;372: 20160088. pmid:28289256
  9. 9. Arunsan P, Ittiprasert W, Smout MJ, Cochran CJ, Mann VH, Chaiyadet S, et al. Programmed knockout mutation of liver fluke granulin attenuates virulence of infection-induced hepatobiliary morbidity. Elife. 2019;8: e41463. pmid:30644359
  10. 10. Yurchenko V, Lukeš J. Parasites and their (endo)symbiotic microbes. Parasitology. 2018;145: 1261–1264. pmid:30086814
  11. 11. Theis KR, Dheilly NM, Klassen JL, Brucker RM, Baines JF, Bosch TCG, et al. Getting the hologenome concept right: an eco-evolutionary framework for hosts and their microbiomes. mSystems. 2016; 1:e00028–16. pmid:27822520
  12. 12. Zilber-Rosenberg I, Rosenberg E. Role of microorganisms in the evolution of animals and plants: the hologenome theory of evolution. FEMS Microb Rev. 2008;32:723–735. pmid:18549407
  13. 13. Bordenstein SR, Theis KR. Host biology in light of the microbiome: ten principles of holobionts and hologenomes. PLoS Biol. 2015;13: e1002226. pmid:26284777
  14. 14. Lukeš J, Stensvold CR, Jirků-Pomajbíková K, Wegener Parfrey L. Are human intestinal eukaryotes beneficial or commensals? PLoS Pathog. 2015;11: e1005039. pmid:26270819
  15. 15. Dheilly NM. Holobiont-holobiont interactions: redefining host-parasite interactions. PLoS Pathog. 2014;10: e1004093. pmid:24992663
  16. 16. Dheilly NM, Poulin R, Thomas F. Biological warfare: microorganisms as drivers of host-parasite interactions. Infect Genet Evol. 2015;34: 251–259. pmid:26026593
  17. 17. Dheilly NM, Bolnick D, Bordenstein SR, Brindley PJ, Figueres C, Holmes EC, et al. Parasite Microbiome Project: systematic investigation of microbiome dynamics within and across parasite-host interactions. mSystems. 2017;2: e00050–17. pmid:28761932
  18. 18. Yilmaz P, Kottmann R, Field D, Knight R, Cole JR, Amaral-Zettler L, et al. Minimum information about a marker gene sequence (MIMARKS) and minimum information about any (x) sequence (MIxS) specifications. Nat Biotechnol. 2011;29: 415–420. pmid:21552244
  19. 19. Bowers RM, Kyrpides NC, Stepanauskas R, Harmon-Smith M, Doud D, Reddy TBK, et al. Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea. Nat Biotechnol. 2017;35: 725–731. pmid:28787424
  20. 20. Roux S, Adriaenssens EM, Dutilh BE, Koonin EV, Kropinski AM, Krupovic M, et al. Minimum Information about an Uncultivated Virus Genome (MIUViG). Nat Biotechnol. 2018;37: 29–37. pmid:30556814
  21. 21. Fichorova RN, Lee Y, Yamamoto HS, Takagi Y, Hayes GR, Goodman RP, et al. Endobiont viruses sensed by the human host—beyond conventional antiparasitic therapy. PLoS ONE. 2012;7: e48418. pmid:23144878
  22. 22. Fichorova RN, Buck OR, Yamamoto HS, Fashemi T, Dawood HY, Fashemi B, et al. The villain team-up or how Trichomonas vaginalis and bacterial vaginosis alter innate immunity in concert. Sex Transm Infect. 2013;89: 460–466. pmid:23903808
  23. 23. Martinez-Hernandez F, Fornas O, Lluesma Gomez M, Bolduc B, de la Cruz Peña MJ, Martínez Martínez J, et al. Single-virus genomics reveals hidden cosmopolitan and abundant viruses. Nat Commun. 2017;8: 15892. pmid:28643787
  24. 24. Edwards RA, Rohwer F. Viral metagenomics. Nat Rev Microbiol. 2005;3: 504–510. pmid:15886693
  25. 25. Wilson WH, Gilg IC, Moniruzzaman M, Field EK, Koren S, LeCleir GR, et al. Genomic exploration of individual giant ocean viruses. ISME J. 2017;11: 1736–1745. pmid:28498373
  26. 26. Carius HJ, Little TJ, Ebert D. Genetic variation in a host-parasite association: potential for coevolution and frequency-dependent selection. Evolution. 2001;55: 1136–1145. pmid:11475049
  27. 27. Spor A, Koren O, Ley R. Unravelling the effects of the environment and host genotype on the gut microbiome. Nat Rev Microbiol. 2011;9: 279–290. pmid:21407244
  28. 28. Shi M, Lin X-D, Tian J-H, Chen L-J, Chen X, Li C-X, et al. Redefining the invertebrate RNA virosphere. Nature. 2016;540: 539–543. pmid:27880757
  29. 29. Welch MJL, Rossetti BJ, Rieken CW, Dewhirst FE, Borisy GG. Biogeography of a human oral microbiome at the micron scale. Proc Natl Acad Sci. 2016;113: E791–E800. pmid:26811460
  30. 30. Jemielita M, Taormina MJ, Burns AR, Hampton JS, Rolig AS, Guillemin K, et al. Spatial and temporal features of the growth of a bacterial species colonizing the zebrafish gut. MBio. 2014;5: e01751–14. pmid:25516613
  31. 31. Ondov BD, Bergman NH, Phillippy AM. Interactive metagenomic visualization in a Web browser. BMC Bioinformatics. 2011;12: 385. pmid:21961884
  32. 32. Rodriguez-R LM, Gunturu S, Tiedje JM, Cole JR, Konstantinidis KT. Nonpareil 3: fast estimation of metagenomic coverage and sequence diversity. mSystems. 2018;3: e00039–18. pmid:29657970
  33. 33. Truong DT, Franzosa EA, Tickle TL, Scholz M, Weingart G, Pasolli E, et al. MetaPhlAn2 for enhanced metagenomic taxonomic profiling. Nat Methods. 2015;12: 902–903. pmid:26418763
  34. 34. Franzosa EA, McIver LJ, Rahnavard G, Thompson LR, Schirmer M, Weingart G, et al. Species-level functional profiling of metagenomes and metatranscriptomes. Nat Methods. 2018;15: 962–968. pmid:30377376
  35. 35. Thompson LR, Sanders JG, McDonald D, Amir A, Ladau J, Locey KJ, et al. A communal catalogue reveals Earth’s multiscale microbial diversity. Nature. 2017;551: 457–463. pmid:29088705
  36. 36. Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. DADA2: high-resolution sample inference from Illumina amplicon data. Nat Methods. 2016;13: 581–583. pmid:27214047
  37. 37. Amir A, McDonald D, Navas-Molina JA, Kopylova E, Morton JT, Zech Xu Z, et al. Deblur rapidly resolves single-nucleotide community sequence patterns. mSystems. 2017;2: e00191–16. pmid:28289731
  38. 38. Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, et al. QIIME allows analysis of high-throughput community sequencing data. Nat Methods. 2010;7: 335–336. pmid:20383131
  39. 39. Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nature Biotechnol. 2019. pmid:31341288
  40. 40. Gonzalez A, Navas-Molina JA, Kosciolek T, McDonald D, Vázquez-Baeza Y, Ackermann G, et al. Qiita: rapid, web-enabled microbiome meta-analysis. Nat Methods. 2018;15: 7968. pmid:30275573
  41. 41. Pleijel F, Jondelius U, Norlinder E, Nygren A, Oxelman B, Schander C, et al. Phylogenies without roots? A plea for the use of vouchers in molecular phylogenetic studies. Mol Phylogenet Evol. 2008;48: 369–371. pmid:18424089
  42. 42. Cristescu ME. From barcoding single individuals to metabarcoding biological communities: towards an integrative approach to the study of global biodiversity. Trends Ecol Evol. 2014;29: 566–571. pmid:25175416
  43. 43. Gilbert JA, Meyer F, Jansson J, Gordon J, Pace N, Tiedje J, et al. The Earth Microbiome Project: meeting report of the “1 EMP meeting on sample selection and acquisition” at Argonne National Laboratory October 6 2010. Stand Genomic Sci. 2010;3: 249–253. pmid:21304728
  44. 44. Klein M, Lanka S, Muller D, Knippers R. Single-stranded regions in the genome of the Ectocarpus siliculosus virus. Virology. 1994;202: 1076–1078. pmid:8030215
  45. 45. Ebert D. The epidemiology and evolution of symbionts with mixed-mode transmission. Annu Rev Ecol Evol Syst. 2013;44: 623–643.
  46. 46. Kreisinger J, Bastien Gr, Hauffe HC, Marchesi J, Perkins SE. Interactions between multiple helminths and the gut microbiota in wild rodents. Philos Trans R Soc Lond B Biol Sci. 2015;370: 20140295. pmid:26150661
  47. 47. Hersch-Green EI, Turley NE, Johnson MTJ. Community genetics: what have we accomplished and where should we be going? Philos Trans R Soc Lond B Biol Sci. 2011;366: 1453–1460. pmid:21444318
  48. 48. Thompson J. The Geographic Mosaic of Coevolution. Chicago, IL, USA: University of Chicago Press; 2005.
  49. 49. King KC, Bonsall MB. The evolutionary and coevolutionary consequences of defensive microbes for host-parasite interactions. BMC Evol Biol. 2017;17: 190. pmid:28806933
  50. 50. Ford SA, King KC. Harnessing the power of defensive microbes: evolutionary implications in nature and disease control. PLoS Pathog. 2016;12: e1005465. pmid:27058881
  51. 51. Dennis AB, Patel V, Oliver KM, Vorburger C. Parasitoid gene expression changes after adaptation to symbiont-protected hosts. Evolution. 2017;71: 2599–2617. pmid:28841224
  52. 52. The Integrative Human Microbiome Project. Dynamic analysis of microbiome-host omics profiles during periods of human health and disease. Cell Host Microbe. 2014;16: 276–289. pmid:25211071
  53. 53. Hahn MA, Dheilly NM. Experimental models to study the role of microbes in host-parasite interactions. Front Microbiol. 2016;7: 1300. pmid:27602023
  54. 54. Dangtakot R, Pinlaor S, Itthitaetrakool U, Chaidee A, Chomvarin C, Sangka A, et al. Coinfection with Helicobacter pylori and Opisthorchis viverrini enhances the severity of hepatobiliary abnormalities in hamsters. Infect Immun. 2017;85(4):e00009–17. pmid:28138021.
  55. 55. Deenonpoe R, Chomvarin C, Pairojkul C, Chamgramol Y, Loukas A, Brindley PJ, et al. The carcinogenic liver fluke Opisthorchis viverrini is a reservoir for species of Helicobacter. APJCP. 2015;16(5):1751–8. pmid:25773821.
  56. 56. Deenonpoe R, Mairiang E, Mairiang P, Pairojkul C, Chamgramol Y, Rinaldi G, et al. Elevated prevalence of Helicobacter species and virulence factors in opisthorchiasis and associated hepatobiliary disease. Sci Rep. 2017;7:42744. pmid:28198451
  57. 57. Fichorova RN, Lee Y, Yamamoto HS, Takagi Y, Hayes GR, Goodman RP, et al. Endobiont viruses sensed by the human host‚ beyond conventional antiparasitic therapy. PLoS ONE. 2012;7(11):e48418. pmid:23144878
  58. 58. Onderdonk AB, Delaney ML, Fichorova RN. The human microbiome during bacterial vaginosis. Clin microbiol rev. 2016;29(2):223–38. Epub 02/10. pmid:26864580.
  59. 59. Ives A, Ronet C, Prevel F, Ruzzante G, Fuertes-Marraco S, Schutz F, et al. Leishmania RNA virus controls the severity of mucocutaneous Leishmaniasis. Science. 2011;331(6018):775–8. pmid:21311023
  60. 60. Adaui V, Lye L-F, Akopyants NS, Zimic M, Llanos-Cuentas A, Garcia L, et al. Association of the endobiont double-stranded RNA virus LRV1 with treatment failure for human Leishmaniasis caused by Leishmania braziliensis in Peru and Bolivia. J Infect Dis. 2015;213(1):112–21. pmid:26123565
  61. 61. Landmann F, Voronin D, Sullivan W, Taylor MJ. Anti-filarial activity of antibiotic therapy is due to extensive apoptosis after Wolbachia depletion from filarial nematodes. PLoS Pathog. 2011;7(11):e1002351. pmid:22072969
  62. 62. Slatko BE, Taylor MJ, Foster JM. The Wolbachia endosymbiont as an anti-filarial nematode target. Symbiosis. 2010;51(1):55–65. Epub 06/05. pmid:20730111.
  63. 63. Gauthier J, Drezen J-M, Herniou EA. The recurrent domestication of viruses: major evolutionary transitions in parasitic wasps. Parasitol. 2017;145(6):713–23. Epub 05/23. pmid:28534452
  64. 64. Dheilly NM, Maure F, Ravallec M, Galinier R, Doyon J, Duval D, et al. Who is the puppet master? Replication of a parasitic wasp-associated virus correlates with host behaviour manipulation. Proc Roy Soc B Biol Sci. 2015;282(1803). pmid:25673681
  65. 65. Tan C-W, Peiffer M, Hoover K, Rosa C, Acevedo FE, Felton GW. Symbiotic polydnavirus of a parasite manipulates caterpillar and plant immunity. Proc Nat Acad Sci. 2018;115(20):5199. pmid:29712862
  66. 66. Gottlieb Y, Lalzar I, Klasson L. Distinctive Genome Reduction Rates Revealed by Genomic analyses of two Coxiella-like endosymbionts in ticks. Genome Biol Evol. 2015;7(6):1779–96. pmid:26025560.
  67. 67. Smith TA, Driscoll T, Gillespie JJ, Raghavan R. A Coxiella-like endosymbiont is a potential vitamin source for the Lone Star tick. Genome Biol Evol. 2015;7(3):831–8. pmid:25618142.
  68. 68. Banin E, Khare SK, Naider F, Rosenberg E. Proline-rich peptide from the coral pathogen Vibrio shiloi that inhibits photosynthesis of zooxanthellae. App Env Microbiol. 2001;67(4):1536.
  69. 69. Hayes KS, Bancroft AJ, Goldrick M, Portsmouth C, Roberts IS, Grencis RK. Exploitation of the intestinal microflora by the parasitic nematode Trichuris muris. Science. 2010;328(5984):1391. pmid:20538949
  70. 70. Holm JB, Sorobetea D, Kiilerich P, Ramayo-Caldas Y, Estellé J, Ma T, et al. Chronic Trichuris muris infection decreases diversity of the intestinal microbiota and concomitantly increases the abundance of Lactobacilli. PLoS ONE. 2015;10(5):e0125495. pmid:25942314
  71. 71. Li RW, Wu S, Li W, Navarro K, Couch RD, Hill D, et al. Alterations in the porcine colon microbiota induced by the gastrointestinal nematode Trichuris suis. Infection and Immunity. 2012;80(6):2150. pmid:22493085
  72. 72. Ramanan D, Bowcutt R, Lee SC, Tang MS, Kurtz ZD, Ding Y, et al. Helminth infection promotes colonization resistance via type 2 immunity. Science. 2016;352(6285):608. pmid:27080105
  73. 73. Vaughan JA, Tkach VV, Greiman SE. Chapter 3—Neorickettsial endosymbionts of the digenea: diversity, transmission and distribution. In: Rollinson D, Hay SI, editors. Adv Parasitol. 79: Academic Press; 2012. p. 253–97.
  74. 74. McNulty SN, Tort JF, Rinaldi G, Fischer K, Rosa BA, Smircich P, et al. Genomes of Fasciola hepatica from the Americas reveal colonization with Neorickettsia endobacteria related to the agents of potomac horse and human sennetsu fevers. PLoS Genet. 2017;13(1):e1006537. pmid:28060841
  75. 75. Gaulke CA, Martins ML, Watral VG, Humphreys IR, Spagnoli ST, Kent ML, et al. A longitudinal assessment of host-microbe-parasite interactions resolves the zebrafish gut microbiome’s link to Pseudocapillaria tomentosa infection and pathology. Microbiome. 2019;7(1):10. pmid:30678738