Phylogenetic Triage and Risk Assessment: How to Predict Emerging Phytoplasma Diseases.

Phytoplasma diseases pose a substantial threat to diverse crops of agricultural importance. Management measures are usually implemented only after the disease has already occurred. Early detection of such phytopathogens, prior to disease outbreak, has rarely been attempted, but would be highly beneficial for phytosanitary risk assessment, disease prevention and mitigation. In this study, we present the implementation of a recently proposed proactive disease management protocol (DAMA: Document, Assess, Monitor, Act) for a group of vector-borne phytopathogens. We used insect samples collected during a recent biomonitoring program in southern Germany to screen for the presence of phytoplasmas. Insects were collected with malaise traps in different agricultural settings. DNA was extracted from these mass trap samples and subjected to PCR-based phytoplasma detection and mitochondrial cytochrome c oxidase subunit I (COI) metabarcoding. Phytoplasma DNA was detected in two out of the 152 insect samples analyzed. Phytoplasma identification was performed using iPhyClassifier based on 16S rRNA gene sequence and the detected phytoplasmas were assigned to 'Candidatus Phytoplasma asteris'-related strains. Insect species in the sample were identified by DNA metabarcoding. By using established databases, checklists, and archives, we documented historical associations and records of phytoplasmas and its hosts in the study region. For the assessment in the DAMA protocol, phylogenetic triage was performed in order to determine the risk for tri-trophic interactions (plant-insect-phytoplasma) and associated disease outbreaks in the study region. A phylogenetic heat map constitutes the basis for risk assessment and was used here to identify a minimum number of seven leafhopper species suggested to be monitored by stakeholders in this region. A proactive stance in monitoring changing patterns of association between hosts and pathogens can be a cornerstone in capabilities to prevent future phytoplasma disease outbreaks. To the best of our knowledge, this is the first time that the DAMA protocol has been applied in the field of phytopathology and vector-borne plant diseases.

Guilt by Association: DNA Barcoding-Based Identification of Potential Plant Hosts of Phytoplasmas from Their Insect Carriers.

Phytoplasmas are small phloem-restricted and insect-transmissible bacteria that infect many plant species, including important crops and ornamental plants, causing severe economic losses. Our previous studies screened phytoplasmas in hundreds of leafhoppers collected from natural habitats worldwide and identified multiple genetically different phytoplasmas in seven leafhopper species (potential insect vectors). As an initial step toward determining the impact of these phytoplasmas on the ecosystem, ribulose 1,5-biphosphate carboxylase large subunit (rbcL), a commonly used plant DNA barcoding marker, was employed to identify the plant species that the phytoplasma-harboring leafhoppers feed on. The DNA of 17 individual leafhoppers was PCR amplified using universal rbcL primers. PCR products were cloned, and five clones per amplicon were randomly chosen for Sanger sequencing. Moreover, Illumina high-throughput sequencing on selected PCR products was conducted and confirmed no missing targets in Sanger sequencing. The nucleotide BLAST results revealed 14 plant species, including six well-known plant hosts of phytoplasmas such as tomato, alfalfa, and maize. The remaining species have not been documented as phytoplasma hosts, expanding our knowledge of potential plant hosts. Notably, the DNA of tomato and maize (apparently cultivated in well-managed croplands) was detected in some phytoplasma-harboring leafhopper species sampled in non-crop lands, suggesting the spillover/spillback risk of phytoplasma strains between crop and non-crop areas. Furthermore, our results indicate that barcoding (or metabarcoding) is a valuable tool to study the three-way interactions among phytoplasmas, plant hosts, and vectors. The findings contribute to a better understanding of phytoplasma host range, host shift, and disease epidemiology.

Comparison of Traditional and Next-Generation Approaches for Uncovering Phytoplasma Diversity, with Discovery of New Groups, Subgroups and Potential Vectors.

Despite several decades' effort to detect and identify phytoplasmas (Mollicutes) using PCR and Sanger sequencing focusing on diseased plants, knowledge of phytoplasma biodiversity and vector associations remains highly incomplete. To improve protocols for documenting phytoplasma diversity and ecology, we used DNA extracted from phloem-feeding insects and compared traditional Sanger sequencing with a next-generation sequencing method, Anchored Hybrid Enrichment (AHE) for detecting and characterizing phytoplasmas. Among 22 of 180 leafhopper samples that initially tested positive for phytoplasmas using qPCR, AHE yielded phytoplasma 16Sr sequences for 20 (19 complete and 1 partial sequence) while Sanger sequencing yielded sequences for 16 (11 complete and 5 partial). AHE yielded phytoplasma sequences for an additional 7 samples (3 complete and 4 partial) that did not meet the qPCR threshold for phytoplasma positivity or yielded non-phytoplasma sequences using Sanger sequencing. This suggests that AHE is more efficient for obtaining phytoplasma sequences. Twenty-three samples with sufficient data were classified into eight 16Sr subgroups (16SrI-B, I-F, I-AO, III-U, V-C, IX-J, XI-C, XXXVII-A), three new subgroups (designated as 16SrVI-L, XV-D, XI-G) and three possible new groups. Our results suggest that screening phloem-feeding insects using qPCR and AHE sequencing may be the most efficient method for discovering new phytoplasmas.

Landscape Composition Affects Elements of Metacommunity Structure for Culicidae Across South-Eastern Illinois.

The interplay among invasive alien vectors and the species assemblage of native potential vectors in areas of range expansion may affect the dynamics of pathogen transmission. In this study we investigate how Aedes albopictus, an invasive mosquito of considerable public health concern fits within mosquito communities at the edge of its range of distribution. This was addressed using a 2-year field survey of mosquitoes in south-eastern Illinois. We found that Ae. albopictus was more broadly distributed in this region than previously realized, with new occurrence records for nine counties. Abundance of this species varied strongly and peaked in locations of low-intermediate overall mosquito species richness. This differed from overall mosquito abundance, as well as abundance of another important vector, Cx. pipiens, for which the abundance-richness relationships were best described with power functions. Metacommunity analyses revealed that mosquito communities showed a non-random distribution with a Clementsian gradient, which suggests a pattern whereby distinct species assemblages are associated with specific habitats or environmental conditions. Land use was a significant underlying factor shaping mosquito community structure and species assemblages. Multivariate analyses showed that while Ae. canadensis and Cx. pipiens complex mosquitoes were associated with high and low proportions of wetlands in the environment, respectively, Ae. albopictus was most strongly associated with urban settlements. This work sheds light on landscape-level processes, such as niche differentiation driven by urban and agricultural development, structuring mosquito communities. We suggest that mosquito community assessments across habitats be incorporated as part of a One Health vector surveillance approach to aid in the goal of prediction and prevention of new and (re-)emerging vector-borne diseases.

Ecological super-spreaders drive host-range oscillations: Omicron and risk space for emerging infectious disease.

The unusual genetic diversity of the Omicron strain has led to speculation about its origin. The mathematical modelling platform developed for the Stockholm Paradigm (SP) indicates strongly that it has retro-colonized humans from an unidentified nonhuman mammal, likely originally infected by humans. The relationship between Omicron and all other SARS-CoV-2 variants indicates oscillations among hosts, a core part of the SP. Such oscillations result from the emergence of novel variants following colonization of new hosts, replenishing and expanding the risk space for disease emergence. The SP predicts that pathogens colonize new hosts using pre-existing capacities. Those events are thus predictable to a certain extent. Novel variants emerge after a colonization and are not predictable. This makes it imperative to take proactive measures for anticipating emerging infectious diseases (EID) and mitigating their impact. The SP suggests a policy protocol, DAMA, to accomplish this goal. DAMA comprises: DOCUMENT to detect pathogens before they emerge in new places or colonize new hosts; ASSESS to determine risk; MONITOR to detect changes in pathogen populations that increase the risk of outbreaks and ACT to prevent outbreaks when possible and minimize their impact when they occur.

Food security and emerging infectious disease: risk assessment and risk management.

Climate change, emerging infectious diseases (EIDs) and food security create a dangerous nexus. Habitat interfaces, assumed to be efficient buffers, are being disrupted by human activities which in turn accelerate the movement of pathogens. EIDs threaten directly and indirectly availability and access to nutritious food, affecting global security and human health. In the next 70 years, food-secure and food-insecure countries will face EIDs driving increasingly unsustainable costs of production, predicted to exceed national and global gross domestic products. Our modern challenge is to transform this business as usual and embrace an alternative vision of the biosphere formalized in the Stockholm paradigm (SP). First, a pathogen-centric focus shifts our vision of risk space, determining how pathogens circulate in realized and potential fitness space. Risk space and pathogen exchange are always heightened at habitat interfaces. Second, apply the document-assess-monitor-act (DAMA) protocol developing strategic data for EID risk, to be translated, synthesized and broadcast as actionable information. Risk management is realized through targeted interventions focused around information exchanged among a community of scientists, policy practitioners of food and public health security and local populations. Ultimately, SP and DAMA protect human rights, supporting food security, access to nutritious food, health interventions and environmental integrity.

Emerging infectious disease: An underappreciated area of strategic concern for food security.

Emerging infectious diseases (EIDs) increasingly threaten global food security and public health. Despite technological breakthroughs, we are losing the battle with (re)emerging diseases as treatment costs and production losses rise. A horizon scan of diseases of crops, livestock, seafood and food-borne illness suggests these costs are unsustainable. The paradigm of coevolution between pathogens and particular hosts teaches that emerging diseases occur only when pathogens evolve specific capacities that allow them to move to new hosts. EIDs ought to be rare and unpredictable, so crisis response is the best we can do. Alternatively, the Stockholm Paradigm suggests that the world is full of susceptible but unexposed hosts that pathogens could infect, given the opportunity. Global climate change, globalized trade and travel, urbanization and land-use changes (often associated with biodiversity loss) increase those opportunities, making EID frequent. We can, however, anticipate their arrival in new locations and their behaviour once they have arrived. We can 'find them before they find us', mitigating their impacts. The DAMA (Document, Assess, Monitor, Act) protocol alters the current reactive stance and embodies proactive solutions to anticipate and mitigate the impacts of EID, extending human and material resources and buying time for development of new vaccinations, medications and control measures.

Screening potential insect vectors in a museum biorepository reveals undiscovered diversity of plant pathogens in natural areas.

Phytoplasmas (Mollicutes, Acholeplasmataceae), vector-borne obligate bacterial plant parasites, infect nearly 1,000 plant species and unknown numbers of insects, mainly leafhoppers (Hemiptera, Deltocephalinae), which play a key role in transmission and epidemiology. Although the plant-phytoplasma-insect association has been evolving for >300 million years, nearly all known phytoplasmas have been discovered as a result of the damage inflicted by phytoplasma diseases on crops. Few efforts have been made to study phytoplasmas occurring in noneconomically important plants in natural habitats. In this study, a subsample of leafhopper specimens preserved in a large museum biorepository was analyzed to unveil potential new associations. PCR screening for phytoplasmas performed on 227 phloem-feeding leafhoppers collected worldwide from natural habitats revealed the presence of 6 different previously unknown phytoplasma strains. This indicates that museum collections of herbivorous insects represent a rich and largely untapped resource for discovery of new plant pathogens, that natural areas worldwide harbor a diverse but largely undiscovered diversity of phytoplasmas and potential insect vectors, and that independent epidemiological cycles occur in such habitats, posing a potential threat of disease spillover into agricultural systems. Larger-scale future investigations will contribute to a better understanding of phytoplasma genetic diversity, insect host range, and insect-borne phytoplasma transmission and provide an early warning for the emergence of new phytoplasma diseases across global agroecosystems.

Identification of Phytoplasmas Representing Multiple New Genetic Lineages from Phloem-Feeding Leafhoppers Highlights the Diversity of Phytoplasmas and Their Potential Vectors.

Phytoplasmas are obligate transkingdom bacterial parasites that infect a variety of plant species and replicate in phloem-feeding insects in the order Hemiptera, mainly leafhoppers (Cicadellidae). The insect capacity in acquisition, transmission, survival, and host range directly determines the epidemiology of phytoplasmas. However, due to the difficulty of insect sampling and the lack of follow-up transmission trials, the confirmed phytoplasma insect hosts are still limited compared with the identified plant hosts. Recently, quantitative polymerase chain reaction (qPCR)-based quick screening of 227 leafhoppers collected in natural habitats unveiled the presence of previously unknown phytoplasmas in six samples. In the present study, 76 leafhoppers, including the six prescreened positive samples, were further examined to identify and characterize the phytoplasma strains by semi-nested PCR. A total of ten phytoplasma strains were identified in leafhoppers from four countries including South Africa, Kyrgyzstan, Australia, and China. Based on virtual restriction fragment length polymorphism (RFLP) analysis, these ten phytoplasma strains were classified into four distinct ribosomal (16Sr) groups (16SrI, 16SrIII, 16SrXIV, and 16SrXV), representing five new subgroups (16SrI-AO, 16SrXIV-D, 16SrXIV-E, 16SrXIV-F, and 16SrXV-C). The results strongly suggest that the newly identified phytoplasma strains not only represent new genetic subgroup lineages, but also extend previously undiscovered geographical distributions. In addition, ten phytoplasma-harboring leafhoppers belonged to seven known leafhopper species, none of which were previously reported insect vectors of phytoplasmas. The findings from this study provide fresh insight into genetic diversity, geographical distribution, and insect host range of phytoplasmas. Further transmission trials and screening of new potential host plants and weed reservoirs in areas adjacent to collection sites of phytoplasma harboring leafhoppers will contribute to a better understanding of phytoplasma transmission and epidemiology.

Multiscale Determinants Drive Parasitization of Drosophilidae by Hymenopteran Parasitoids in Agricultural Landscapes.

(1) The management of agricultural landscapes for pest suppression requires a thorough understanding of multiple determinants controlling their presence. We investigated the ecological preferences of indigenous parasitoids and their drosophilid hosts to understand the role of native parasitoids as biological control agents of the invasive frugivorous Drosophila suzukii. (2) Using data from an extensive field survey across different habitat types we analyzed the influence of abiotic and biotic factors on parasitoid and drosophilid communities at multiscale levels. (3) Eight parasitoid and 27 drosophilid species were identified. Thirty-four percent variation in drosophilid communities was explained by factors at the landscape scale, and 52% of significant variation of parasitoids by local distribution of three drosophilid species, mainly collected in woodland. Parasitoid communities were significantly influenced by microhabitat type (ground versus canopy) rather than habitat type. All parasitoids except Pachycrepoideus vindemmiae preferred the ground microhabitat. All parasitoids, with the exception of Trichopria drosophilae and Spalangia erythromera, displayed significant preferences among the drosophilid species used in the baited traps. (4) Since they can tolerate a broad range of habitat factors, altogether pupal parasitoids investigated in this study could play a role in biological control programs to suppress D. suzukii, but non-target effects have to be regarded.

A timetree for phytoplasmas (Mollicutes) with new insights on patterns of evolution and diversification.

The first comprehensive timetree is presented for phytoplasmas, a diverse group of obligate intracellular bacteria restricted to phloem sieve elements of vascular plants and tissues of their hemipteran insect vectors. Maximum likelihood-based phylogenetic analysis of DNA sequence data from the 16S rRNA and methionine aminopeptidase (map) genes yielded well resolved estimates of phylogenetic relationships among major phytoplasma lineages, 16Sr groups and known strains of phytoplasmas. Age estimates for divergences among two major lineages of Mollicutes based on a previous comprehensive bacterial timetree were used to calibrate an initial 16S timetree. A separate timetree was estimated based on the more rapidly-evolving map gene, with an internal calibration based on a recent divergence within two related 16Sr phytoplasma subgroups in group 16SrV thought to have been driven by the introduction of the North American leafhopper vector Scaphoideus titanus Ball into Europe during the early part of the 20th century. Combining the resulting divergence time estimates into a final 16S timetree suggests that evolutionary rates have remained relatively constant overall through the evolution of phytoplasmas and that the origin of this lineage, at ~641 million years ago (Ma), preceded the origin of land plants and hemipteran insects. Nevertheless, the crown group of phytoplasmas is estimated to have begun diversifying ~316 Ma, roughly coinciding with the origin of seed plants and Hemiptera. Some phytoplasma groups apparently associated with particular plant families or insect vector lineages generally arose more recently than their respective hosts and vectors, suggesting that vector-mediated host shifts have been an important mechanism in the evolutionary diversification of phytoplasmas. Further progress in understanding macroevolutionary patterns in phytoplasmas is hindered by large gaps in knowledge of the identity of competent vectors and lack of data on phytoplasma associations with non-economically important plants.

An online global database of Hemiptera-Phytoplasma-Plant biological interactions.

BACKGROUND: Phytoplasmas are phloem-limited plant pathogenic bacteria in the class Mollicutes transmitted by sap-feeding insect vectors of the Order Hemiptera. Vectors still have not yet been identified for about half of the 33 known phytoplasma groups and this has greatly hindered efforts to control the spread of diseases affecting important crops. Extensive gaps of knowledge on actual phytoplasma vectors and on the plant disease epidemiology prevent our understanding of the basic underlying biological mechanisms that facilitate interactions between insects, phytoplasmas and their host plants. NEW INFORMATION: This paper presents a complete online database of Hemiptera-Phytoplasma-Plant (HPP) biological interactions worldwide, searchable via an online interface. The raw data are available through Zenodo at https://doi.org/10.5281/zenodo.2532738. The online database search interface was created using the 3I software (Dmitriev 2006) which enhances data usability by providing a customised web interface (http://trivellone.speciesfile.org/) that provides an overview of the recorded biological interactions and ability to discover particular interactions by searching for one or more phytoplasma, insect or plant taxa. The database will facilitate synthesis of all available and relevant data on the observed associations between phytoplasmas and their insect and plant hosts and will provide useful data to generate and test ecological and evolutionary hypotheses.

Factors shaping community assemblages and species co-occurrence of different trophic levels.

Species assemblages are the results of various processes, including dispersion and habitat filtering. Disentangling the effects of these different processes is challenging for statistical analysis, especially when biotic interactions should be considered. In this study, we used plants (producers) and leafhoppers (phytophagous) as model organisms, and we investigated the relative importance of abiotic versus biotic factors that shape community assemblages, and we infer on their biotic interactions by applying three-step statistical analysis. We applied a novel statistical analysis, that is, multiblock Redundancy Analysis (mbRA, step 1) and showed that 51.8% and 54.1% of the overall variation in plant and leafhopper assemblages are, respectively, explained by the two multiblock models. The most important blocks of variables to explain the variations in plant and leafhopper assemblages were local topography and biotic factors. Variation partitioning analysis (step 2) showed that pure abiotic filtering and pure biotic processes were relatively less important than their combinations, suggesting that biotic relationships are strongly structured by abiotic conditions. Pairwise co-occurrence analysis (step 3) on generalist leafhoppers and the most common plants identified 40 segregated species pairs (mainly between plant species) and 16 aggregated pairs (mainly between leafhopper species). Pairwise analysis on specialist leafhoppers and potential host plants clearly revealed aggregated patterns. Plant segregation suggests heterogeneous resource availability and competitive interactions, while leafhopper aggregation suggests host feeding differentiation at the local level, different feeding microhabitats on host plants, and similar environmental requirements of the species. Using the novel mbRA, we disentangle for the first time the relative importance of more than five distinct groups of variables shaping local species communities. We highlighted the important role of abiotic processes mediated by bottom-up effects of plants on leafhopper communities. Our results revealed that in-field structure diversification and trophic interactions are the main factors causing the co-occurrence patterns observed.

Spatial Distribution and Sampling Plans for Grapevine Plant Canopy-Inhabiting Scaphoideus titanus (Hemiptera: Cicadellidae) Nymphs.

The paper deals with the study of the spatial distribution and the design of sampling plans for estimating nymph densities of the grape leafhopper Scaphoideus titanus Ball in vine plant canopies. In a reference vineyard sampled for model parameterization, leaf samples were repeatedly taken according to a multistage, stratified, random sampling procedure, and data were subjected to an ANOVA. There were no significant differences in density neither among the strata within the vineyard nor between the two strata with basal and apical leaves. The significant differences between densities on trunk and productive shoots led to the adoption of two-stage (leaves and plants) and three-stage (leaves, shoots, and plants) sampling plans for trunk shoots- and productive shoots-inhabiting individuals, respectively. The mean crowding to mean relationship used to analyze the nymphs spatial distribution revealed aggregated distributions. In both the enumerative and the sequential enumerative sampling plans, the number of leaves of trunk shoots, and of leaves and shoots of productive shoots, was kept constant while the number of plants varied. In additional vineyards data were collected and used to test the applicability of the distribution model and the sampling plans. The tests confirmed the applicability 1) of the mean crowding to mean regression model on the plant and leaf stages for representing trunk shoot-inhabiting distributions, and on the plant, shoot, and leaf stages for productive shoot-inhabiting nymphs, 2) of the enumerative sampling plan, and 3) of the sequential enumerative sampling plan. In general, sequential enumerative sampling was more cost efficient than enumerative sampling.