Variation and correlations between sexual, asexual and natural enemy resistance life-history traits in a natural plant pathogen population.

BACKGROUND: Understanding the mechanisms by which diversity is maintained in pathogen populations is critical for epidemiological predictions. Life-history trade-offs have been proposed as a hypothesis for explaining long-term maintenance of variation in pathogen populations, yet the empirical evidence supporting trade-offs has remained mixed. This is in part due to the challenges of documenting successive pathogen life-history stages in many pathosystems. Moreover, little is understood of the role of natural enemies of pathogens on their life-history evolution. RESULTS: We characterize life-history-trait variation and possible trade-offs in fungal pathogen Podosphaera plantaginis infecting the host plant Plantago lanceolata. We measured the timing of both asexual and sexual stages, as well as resistance to a hyperparasite of seven pathogen strains that vary in their prevalence in nature. We find significant variation among the strains in their life-history traits that constitute the infection cycle, but no evidence for trade-offs among pathogen development stages, apart from fast pathogen growth coninciding with fast hyperparasite growth. Also, the seemingly least fit pathogen strain was the most prevalent in the nature. CONCLUSIONS: We conclude that in the nature environmental variation, and interactions with the antagonists of pathogens themselves may maintain variation in pathogen populations.

Role of Temperature and Coinfection in Mediating Pathogen Life-History Traits.

Understanding processes maintaining variation in pathogen life-history traits is a key challenge in disease biology, and of importance for predicting when and where risks of disease emergence are highest. Pathogens are expected to encounter tremendous levels of variation in their environment - both abiotic and biotic - and this variation may promote maintenance of variation in pathogen populations through space and time. Here, we measure life-history traits of an obligate fungal pathogen at both asexual and sexual stages under both single infection and coinfection along a temperature gradient. We find that temperature had a significant effect on all measured life-history traits while coinfection only had a significant effect on the number of sexual resting structures produced. The effect of temperature on life-history traits was both direct as well as mediated through a genotype-by-temperature interaction. We conclude that pathogen life-history traits vary in their sensitivity to abiotic and biotic variation in the environment.

Tick-borne pathogens of zoonotic and veterinary importance in Nigerian cattle.

BACKGROUND: Ticks and tick-borne diseases undermine cattle fitness and productivity in the whole of sub-Saharan Africa, including Nigeria. In this West African country, cattle are challenged by numerous tick species, especially during the wet season. Consequently, several TBDs are known to be endemic in Nigerian cattle, including anaplasmosis, babesiosis, cowdriosis and theilerioris (by Theileria mutans and Theileria velifera). To date, all investigations on cattle TBDs in Nigeria have been based on cytological examinations and/or on serological methods. This study aimed to ascertain the occurrence of tick-borne pathogens of veterinary and zoonotic importance in cattle in Nigeria using molecular approaches. METHODS: In October 2008, 704 whole blood samples were collected from indigenous cattle in the Plateau State, Nigeria. Analysis for tick-borne pathogens was conducted by means of PCR-based reverse line blotting (RLB) and sequencing targeting a panel of five genera of microorganisms (i.e. Babesia, Theileria, Anaplasma, Ehrlichia and Rickettsia spp.). RESULTS: In total, 561/704 (82.6%) animals were found infected, with 465 (69.6%) of them being infected by two or more microorganisms, with up to 77 possible combinations of pathogens detected. Theileria mutans was the most prevalent microorganism (66.3%), followed by Theileria velifera (52.4%), Theileria taurotragi (39.5%), Anaplasma marginale (39.1%), Anaplasma sp. (Omatjenne) (34.7%), Babesia bigemina (7.9%), Anaplasma centrale (6.3%), Anaplasma platys (3.9%), Rickettsia massiliae (3.5%), Babesia bovis (2.0%) and Ehrlichia ruminantium (1.1%). Calves were found significantly less infected than juvenile and adult cattle. CONCLUSIONS: This study provides updated, molecular-based information on cattle TBDs in Nigeria. The molecular approach employed allowed the diagnosis of numerous positive cases including carrier statuses, multiple infections and novel pathogen detections within the indigenous cattle population. Moreover, the RLB method here described enabled the detection of veterinary agents not only pertaining to bovine health, including also those of zoonotic importance. The high prevalence recorded for T. mutans, T. velifera, A. marginale, T. taurotragi and Anaplasma sp. (Omatjenne), suggests they may be endemically established in Nigeria, whereas the lower prevalence recorded for other microorganisms (i.e. A. centrale and B. bovis) highlights a less stable epidemiological scenario, requiring further investigations.

Co-infection of Ticks: The Rule Rather Than the Exception.

INTRODUCTION: Ticks are the most common arthropod vectors of both human and animal diseases in Europe, and the Ixodes ricinus tick species is able to transmit a large number of bacteria, viruses and parasites. Ticks may also be co-infected with several pathogens, with a subsequent high likelihood of co-transmission to humans or animals. However few data exist regarding co-infection prevalences, and these studies only focus on certain well-known pathogens. In addition to pathogens, ticks also carry symbionts that may play important roles in tick biology, and could interfere with pathogen maintenance and transmission. In this study we evaluated the prevalence of 38 pathogens and four symbionts and their co-infection levels as well as possible interactions between pathogens, or between pathogens and symbionts. METHODOLOGY/PRINCIPAL FINDINGS: A total of 267 Ixodes ricinus female specimens were collected in the French Ardennes and analyzed by high-throughput real-time PCR for the presence of 37 pathogens (bacteria and parasites), by rRT-PCR to detect the presence of Tick-Borne encephalitis virus (TBEV) and by nested PCR to detect four symbionts. Possible multipartite interactions between pathogens, or between pathogens and symbionts were statistically evaluated. Among the infected ticks, 45% were co-infected, and carried up to five different pathogens. When adding symbiont prevalences, all ticks were infected by at least one microorganism, and up to eight microorganisms were identified in the same tick. When considering possible interactions between pathogens, the results suggested a strong association between Borrelia garinii and B. afzelii, whereas there were no significant interactions between symbionts and pathogens. CONCLUSION/SIGNIFICANCE: Our study reveals high pathogen co-infection rates in ticks, raising questions about possible co-transmission of these agents to humans or animals, and their consequences to human and animal health. We also demonstrated high prevalence rates of symbionts co-existing with pathogens, opening new avenues of enquiry regarding their effects on pathogen transmission and vector competence.

The importance of multiparasitism: examining the consequences of co-infections for human and animal health.

Most parasites co-occur with other parasites, although the importance of such multiparasitism has only recently been recognised. Co-infections may result when hosts are independently infected by different parasites at the same time or when interactions among parasite species facilitate co-occurrence. Such interactions can have important repercussions on human or animal health because they can alter host susceptibility, infection duration, transmission risks, and clinical symptoms. These interactions may be synergistic or antagonistic and thus produce diverse effects in infected humans and animals. Interactions among parasites strongly influence parasite dynamics and therefore play a major role in structuring parasite populations (both within and among hosts) as well as host populations. However, several methodological challenges remain when it comes to detecting parasite interactions. The goal of this review is to summarise current knowledge on the causes and consequences of multiparasitism and to discuss the different methods and tools that researchers have developed to study the factors that lead to multiparasitism. It also identifies new research directions to pursue.

To be or not to be associated: power study of four statistical modeling approaches to identify parasite associations in cross-sectional studies.

A growing number of studies are reporting simultaneous infections by parasites in many different hosts. The detection of whether these parasites are significantly associated is important in medicine and epidemiology. Numerous approaches to detect associations are available, but only a few provide statistical tests. Furthermore, they generally test for an overall detection of association and do not identify which parasite is associated with which other one. Here, we developed a new approach, the association screening approach, to detect the overall and the detail of multi-parasite associations. We studied the power of this new approach and of three other known ones (i.e., the generalized chi-square, the network and the multinomial GLM approaches) to identify parasite associations either due to parasite interactions or to confounding factors. We applied these four approaches to detect associations within two populations of multi-infected hosts: (1) rodents infected with Bartonella sp., Babesia microti and Anaplasma phagocytophilum and (2) bovine population infected with Theileria sp. and Babesia sp. We found that the best power is obtained with the screening model and the generalized chi-square test. The differentiation between associations, which are due to confounding factors and parasite interactions was not possible. The screening approach significantly identified associations between Bartonella doshiae and B. microti, and between T. parva, T. mutans, and T. velifera. Thus, the screening approach was relevant to test the overall presence of parasite associations and identify the parasite combinations that are significantly over- or under-represented. Unraveling whether the associations are due to real biological interactions or confounding factors should be further investigated. Nevertheless, in the age of genomics and the advent of new technologies, it is a considerable asset to speed up researches focusing on the mechanisms driving interactions between parasites.

A probabilistic model in cross-sectional studies for identifying interactions between two persistent vector-borne pathogens in reservoir populations.

BACKGROUND: In natural populations, individuals are infected more often by several pathogens than by just one. In such a context, pathogens can interact. This interaction could modify the probability of infection by subsequent pathogens. Identifying when pathogen associations correspond to biological interactions is a challenge in cross-sectional studies where the sequence of infection cannot be demonstrated. METHODOLOGY/PRINCIPAL FINDINGS: Here we modelled the probability of an individual being infected by one and then another pathogen, using a probabilistic model and maximum likelihood statistics. Our model was developed to apply to cross-sectional data, vector-borne and persistent pathogens, and to take into account confounding factors. Our modelling approach was more powerful than the commonly used Chi-square test of independence. Our model was applied to detect potential interaction between Borrelia afzelii and Bartonella spp. that infected a bank vole population at 11% and 57% respectively. No interaction was identified. CONCLUSIONS/SIGNIFICANCE: The modelling approach we proposed is powerful and can identify the direction of potential interaction. Such an approach can be adapted to other types of pathogens, such as non-persistents. The model can be used to identify when co-occurrence patterns correspond to pathogen interactions, which will contribute to understanding how organism communities are assembled and structured. In the long term, the model's capacity to better identify pathogen interactions will improve understanding of infectious risk.

Co-infection of Borrelia afzelii and Bartonella spp. in bank voles from a suburban forest.

We report the molecular detection of Borrelia afzelii (11%) and Bartonella spp. (56%) in 447 bank voles trapped in a suburban forest in France. Adult voles were infected by significantly more Borrelia afzelii than juveniles (p<0.001), whereas no significant difference was detected in the prevalence of Bartonella spp. between young and adult individuals (p=0.914). Six percent of the animals were co-infected by both bacteria. Analysis of the bank vole carrier status for either pathogen indicated that co-infections occur randomly (p=0.94, CI(95)=[0.53; 1.47]). Sequence analysis revealed that bank voles were infected by a single genotype of Borrelia afzelii and by 32 different Bartonella spp. genotypes, related to three known species specific to rodents (B. taylorii, B. grahamii and B. doshiae) and also two as yet unidentified Bartonella species. Our findings confirm that rodents harbor high levels of potential human pathogens; therefore, widespread surveillance should be undertaken in areas where humans may encounter rodents.

Host races in Ixodes ricinus, the European vector of Lyme borreliosis.

Ixodes ricinus is a European tick that transmits numerous pathogenic agents, including the bacteria that cause Lyme disease (some genospecies of Borrelia burgdorferi sensu lato complex). This tick has been considered as a classic example of an extreme generalist vector. However, host-associations in such vector species are difficult to determine from field observations alone and recent work suggests that host specificity may be more frequent in ticks than previously thought. The presence of host-associated vector groups can significantly alter the circulation and evolutionary pathway of associated pathogens. In this paper, we explicitly test for host-associated genetic structure in I. ricinus. We analyzed genetic variability at 11 microsatellite markers in a large sample of ticks collected directly from trapped wild animals (birds, rodents, lizards, wild boar and roe deer) at five sites in Western and Central Europe. We found significant levels of genetic structure both among host individuals and among host types within local populations, suggesting that host use is not random in I. ricinus. These results help explain previous patterns of structure found in off-host tick samples, along with epidemiological observations of Lyme disease.