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Weeds, as ancillary hosts, pose disproportionate risk for virulent pathogen transfer to crops.

ABSTRACT: BACKGROUND:The outcome of the arms race between hosts and pathogens depends heavily on the interactions between their genetic diversity, population size and transmission ability. Theory predicts that genetically diverse hosts will select for higher virulence and more diverse pathogens than hosts with low genetic diversity. Cultivated hosts typically have lower genetic diversity and thus small effective population sizes, but can potentially harbour large pathogen population sizes. On the other hand, hosts, such as weeds, which are genetically more diverse and thus have larger effective population sizes, usually harbour smaller pathogen population sizes. Large pathogen population sizes may lead to more opportunities for mutation and hence more diverse pathogens. Here we test the predictions that pathogen neutral genetic diversity will increase with large pathogen population sizes and host diversity, whereas diversity under selection will increase with host diversity. We assessed and compared the diversity of a fungal pathogen, Rhynchosporium commune, on weedy barley grass (which have a large effective population size) and cultivated barley (low genetic diversity) using microsatellites, effector locus nip1 diversity and pathogen aggressiveness in order to assess the importance of weeds in the evolution of the neutral and selected diversity of pathogens. RESULTS:The findings indicated that the large barley acreage and low host diversity maintains higher pathogen neutral genetic diversity and lower linkage disequilibrium, while the weed maintains more pathotypes and higher virulence diversity at nip1. Strong evidence for more pathogen migration from barley grass to barley suggests transmission of virulence from barley grass to barley is common. CONCLUSIONS:Pathogen census population size is a better predictor for neutral genetic diversity than host diversity. Despite maintaining a smaller pathogen census population size, barley grass acts as an important ancillary host to R. commune, harbouring highly virulent pathogen types capable of transmission to barley. Management of disease on crops must therefore include management of weedy ancillary hosts, which may harbour disproportionate supplies of virulent pathogen strains.

SUBMITTER: Linde CC

PROVIDER: S-EPMC4866072 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

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Weeds, as ancillary hosts, pose disproportionate risk for virulent pathogen transfer to crops.

Linde Celeste C CC Smith Leon M LM Peakall Rod R

BMC evolutionary biology 20160512

<h4>Background</h4>The outcome of the arms race between hosts and pathogens depends heavily on the interactions between their genetic diversity, population size and transmission ability. Theory predicts that genetically diverse hosts will select for higher virulence and more diverse pathogens than hosts with low genetic diversity. Cultivated hosts typically have lower genetic diversity and thus small effective population sizes, but can potentially harbour large pathogen population sizes. On the ...[more]

PMID: 27176034

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Project description:Weeds surrounding crops may act as alternative hosts, playing important epidemiological roles as virus reservoirs and impacting virus evolution. We used high-throughput sequencing to identify viruses in Spanish melon crops and plants belonging to three pluriannual weed species, Ecballium elaterium, Malva sylvestris, and Solanum nigrum, sampled at the edges of the crops. Melon and E. elaterium, both belonging to the family Cucurbitaceae, shared three virus species, whereas there was no virus species overlap between melon and the other two weeds. The diversity of cucurbit aphid-borne yellows virus (CABYV) and tomato leaf curl New Delhi virus (ToLCNDV), both in melon and E. elaterium, was further studied by amplicon sequencing. Phylogenetic and population genetics analyses showed that the CABYV population was structured by the host, identifying three sites in the CABYV RNA-dependent RNA polymerase under positive selection, perhaps reflecting host adaptation. The ToLCNDV population was much less diverse than the CABYV one, likely as a consequence of the relatively recent introduction of ToLCNDV in Spain. In spite of its low diversity, we identified geographical but no host differentiation for ToLCNDV. Potential virus migration fluxes between E. elaterium and melon plants were also analyzed. For CABYV, no evidence of migration between the populations of the two hosts was found, whereas important fluxes were identified between geographically distant subpopulations for each host. For ToLCNDV, in contrast, evidence of migration from melon to E. elaterium was found, but not the other way around. IMPORTANCE It has been reported that about half of the emerging diseases affecting plants are caused by viruses. Alternative hosts often play critical roles in virus emergence as virus reservoirs, bridging host species that are otherwise unconnected and/or favoring virus diversification. In spite of this, the viromes of potential alternative hosts remain largely unexplored. In the case of crops, pluriannual weeds at the crop edges may play these roles. Here, we took advantage of the power of high-throughput sequencing to characterize the viromes of three weed species frequently found at the edges of melon crops. We identified three viruses shared by melon and the cucurbit weed, with two of them being epidemiologically relevant for melon crops. Further genetic analyses showed that these two viruses had contrasting patterns of diversification and migration, providing an interesting example on the role that weeds may play in the ecology and evolution of viruses affecting crops.

Project description:Ketoprofen and diclofenac are non-steroidal anti-inflammatory drugs (NSAIDs) often used for similar indications, and both are frequently found in surface waters. Diclofenac affects organ histology and gene expression in fish at around 1 M-BM-5g/L. Here, we exposed rainbow trout to ketoprofen (1, 10 and 100 M-BM-5g/L) to investigate if this alternative causes less risk for pharmacological responses in fish. The bioconcentration factor from water to fish blood plasma was <0.05 (4 for diclofenac based on previous studies). Ketoprofen only reached up to 0.6M-bM-^@M-0 of the human therapeutic plasma concentration, thus the probability of target-related effects was estimated to be fairly low. Accordingly, a comprehensive analysis of hepatic gene expression revealed no consistent responses. In some contrast, trout exposed to undiluted, treated sewage effluents bioconcentrated ketoprofen and other NSAIDs much more efficiently, according to a meta-analysis of recent studies. Neither of the setups is however an ideal representation of the field situation. If a controlled exposure system with a single chemical in pure water is a reasonable representation of the environment, then the use of ketoprofen is likely to pose a lower risk for wild fish than diclofenac, but if bioconcentration factors from effluent-exposed fish are applied, the risks may be more similar. Ketoprofen (purity M-bM-^IM-%98%) (Sigma-Aldrich, Steinheim, Germany) was dissolved in water (500 mg/L concentrated solution), stirred vigorously and diluted stepwise to obtain stock concentrations (0.5 mg/L, 5 mg/L and 50 mg/L). Juvenile rainbow trout (Oncorhynchus mykiss) of both sexes (age: approximately six months, weight: 39.4M-BM-16.6g) were obtained from VM-CM-$nneM-CM-%ns fiskodling AB, Sweden, and kept in 500 L holding tanks with sand-filtered, aerated fresh water in a flow-through system for one week prior to the experiment. Eight experimental 48 L glass aquaria, semi-covered in black plastic bags to reduce visual stress from the outside (12:12 h light:dark photocycle), were supplied with filtered, aerated freshwater at a flow rate of 0.25 L/min. At the onset of the experiment 80 trout were randomly divided among the aquaria (ten fish in each). Peristaltic pumps (500 M-BM-5l/min) from each stock solution were used to reach target ketoprofen concentrations of 0 (control), 1 (low), 10 (intermediate) and 100 (high) M-BM-5g/L with two aquaria for each concentration. Water samples were taken from each aquarium at day 1, 7 and 14 and stored at -20M-BM-0C until analysis. To minimize biological variation due to variable food intake, the fish were not fed during the exposure period. It should be stressed that trout readily cope with food deprivation for much longer periods at these temperatures [Kullgren et al., 2010]. To ensure a stable water quality, temperature (12.9M-BM-10.1M-BM-0C), pH (7.4M-BM-10.2) and oxygen saturation (88.3%M-BM-11.3) were monitored every third day. The total organic carbon content of the supply water was 2.5 mg/L. At the experiment termination on day 14, the fish were killed by a rapid blow to the head and blood was collected from the caudal vessels by the use of heparinized syringes. The plasma was instantly separated by centrifugation at 10,000 rpm for 2 min and snap frozen in liquid nitrogen. The length and weight of the fish were measured and their sex determined by macroscopical observation of their gonads. Liver samples for gene expression analyses were collected and snap frozen in liquid nitrogen. Both liver and plasma samples were stored at M-bM-^HM-^R70M-BM-0C until analysis. All animal experiments were approved by the local animal committee in Gothenburg (permission number 216-2010). A 15k rainbow trout gene expression microarray was designed for the RT analyzer platform (febit, Heidelberg, Germany) using The Institute for Genomic Research (TIGR) Rainbow Trout Gene Index (RTGI) database version 7.0 (http://compbio.dfci.harvard.edu/tgi/). Details on the probe design strategy, but for eelpout (Zoarces viviparus), and transcript selection strategy are described elsewhere [Cuklev et al., 2011, Kristiansson et al., 2009, Cuklev et al., 2012]. When available, transcripts at GenBank (http://www.ncbi.nlm.nih.gov/nucleotide) were used. Results from similar microarrays, performed by our research group using the same platform, have shown good correlation with qPCR data [Cuklev et al., Kristiansson et al., 2009, Cuklev et al., 2012, Gunnarsson et al., 2009, Lennquist et al., 2011]. The frozen liver tissue was homogenized using Tissuelyser (Qiagen) and total hepatic RNA was isolated using QIAcube and RNeasyM-BM-. Plus Mini Kit (Qiagen). The RNA quantity was determined with spectophotometric measurements (Nanodrop 1000, NanoDrop Technologies) and the quality was assessed by Experion automated electrophoresis using RNA StdSense chip (Bio-Rad, Sundbyberg, Sweden). Biotinylated aRNA was synthesized using MessageAmpM-bM-^DM-" II-Biotin Enhanced Single Round aRNA Amplification Kit (AmbionM-BM-.). The aRNA samples (20 M-BM-5g) were vacuum dried in a vacuum centrifuge, dissolved in 10 M-BM-5l water and fragmented according to the manufacturerM-bM-^@M-^Ys protocol. The following steps described in this subchapter were all performed by febit. Oligonucleotide arrays were synthesized by photo-controlled in situ synthesis using the Geniom One system (febit). Each biochip consists of eight individually accessible micro-channels, each of which is referred to as a microarray in this manuscript. Four individuals (of both sexes) from each control aquarium and each high exposure concentration aquarium were included in the analysis, i.e. eight fish per exposure concentration. In total, two biochips were analyzed corresponding to 16 microarrays. Pre-hybridization and hybridization were performed based on a customized protocol, described in detail by Cuklev et al. [2011]. The samples were randomly allocated on the biochips. Signals were detected using the internal CCD-camera system of the RT analyzer instrument (febit) and quantified using the Geniom Wizard software. Integration times were 266 and 273 ms, determined automatically by the instrument software. All statistical calculations were done in R-2.12.2 (www.r-project.org) [R Development Core Team, 2010]. The quality of pre- and post-normalized arrays was verified with Box and MA plots. The data analysis was performed in the R-package LIMMA [Smyth, 2004]. Data were normalized using the M-bM-^@M-^XquantileM-bM-^@M-^Y method. Moderated t-statistics and adjusted p-values of differential expression were calculated using the empirical Bayes model. As we found no clear differences between the two control aquaria or between the two aquaria with the highest concentration of ketoprofen (100 M-BM-5g/L), all fish from the same treatment were treated as a single group, i.e. we compared one control group to one group of fish exposed to 100 M-BM-5g/L of ketoprofen.

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Weeds, as ancillary hosts, pose disproportionate risk for virulent pathogen transfer to crops.

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Weeds, as ancillary hosts, pose disproportionate risk for virulent pathogen transfer to crops.

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