TRANSGENERATIONAL EFFECTS OF HOST PLANT SWITCHING AND ASTER YELLOWS PHYTOPLASMA INFECTION ON THE FITNESS AND MICROBIOME OF THE ASTER LEAFHOPPER (Macrosteles quadrilineatus)
Notice bibliographique
Résumé
Vector–pathogen–plant interactions shape the risk and severity of Aster Yellows (AY) outbreaks in Prairie agroecosystems. This thesis tested how the aster leafhopper (ALH), Macrosteles quadrilineatus (Hemiptera: Cicadellidae) infection by the aster yellows phytoplasma, ‘Candidatus Phytoplasma asteris’ (AYp), and host plants use jointly influence vector fitness and microbiome composition under controlled conditions. Two experiments were conducted. In the first experiment, AYp effects on reproduction, development, and bacterial communities were evaluated by confirming adult infection status using probe-based qPCR and confining pre-sexed AYp-infected or uninfected pairs to individual barley plants for seven days for mating and oviposition; nymphs were counted at 3-day intervals and development was summarized using a Growth Index (GI). Microbiomes of pooled adults were characterized using 16S rRNA gene sequencing and analyzed in QIIME 2 to quantify alpha diversity, beta diversity, and genus-level composition. AYp infection increased fecundity, while GI did not differ between treatments, indicating a reproductive advantage without a detectable change in developmental rate. Microbiome profiles suggested broader treatment-level lineage representation in AYp-infected ALH, whereas AYp-uninfected ALH showed higher within-sample richness and evenness; however, beta diversity did not clearly separate infection treatments and communities remained dominated by the obligate nutritional symbionts ‘Candidatus Sulcia’ and ‘Candidatus Nasuia’. Infection effects were expressed mainly as shifts in relative abundance, with infected insects showing stronger dominance by obligate symbionts and AYp-uninfected ALHs carrying higher proportions of facultative associates including ‘Candidatus Berkiella’, Arsenophonus, and Cardinium. In the second experiment, host plants effect on fitness and microbiomes were tested across five generations using a transgenerational host-switching design in which three parental colonies (F0) were maintained on barley, wheat, and fleabane and fifth-instar nymphs from each colony were transferred into no-choice cup cages on either their natal host or a novel host (barley, wheat, fleabane, or dandelion). Nymphs were reared to adulthood, three male–female pairs per cage were allowed to oviposit for seven days, and offspring emergence was tracked every three days to the fifth instar (19–23 days) to estimate fecundity and calculate GI; this cycle was repeated through F₂–F₄ with host switching imposed at each fifth-instar transfer, and all lineages were returned to their natal host at F₅. Dandelion functioned as a dead-end host, with very low fecundity and GI in F₁ and no lineage persistence beyond that generation, whereas barley, wheat, and fleabane supported development across all generations, but reproductive output diverged progressively, with differences becoming more pronounced through F₃–F₄ and clearest by F₅. Microbiome trajectories paralleled these multigenerational fitness patterns, with alpha diversity increasing from early to late generations and beta diversity shifting most strongly across generations rather than in direct response to host species at a single time point; the magnitude and timing of these changes depended on colony of origin, switching lineage, generation, and their interactions. Early generations were relatively enriched in facultative associates such as ‘Candidatus Berkiella’ and Arsenophonus, whereas later generations showed increasing dominance of the obligate symbionts ‘Candidatus Sulcia’ and ‘Candidatus Nasuia’, indicating that long-term diet history and lineage background jointly shape symbiont restructuring. Overall, these findings show that AYp infection can enhance reproductive performance through subtle rebalancing within a conserved symbiont core and that multigenerational host plant history, more than host identity at a single time point, is a major driver of microbiome organization and long-term offspring fitness, providing mechanistic insight relevant to forecasting and managing AYp risk in Prairie agriculture.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».