Community interactions among microbes give rise to host-microbiome mutualisms in an aquatic plant
Notice bibliographique
Résumé
ABSTRACT Microbiomes often benefit plants, conferring resistance to pathogens, improving stress tolerance, or promoting plant growth. As potential plant mutualists, however, microbiomes are not a single organism but a community of species with complex interactions among microbial taxa and between microbes and their shared host. The nature of ecological interactions among microbes in the microbiome can have important consequences for the net effects of microbiomes on hosts. Here, we compared the effects of individual microbial strains and 10-strain synthetic communities on microbial productivity and host growth using the common duckweed Lemna minor and a synthetic, simplified version of its native microbiome. Except for Pseudomonas protegens , which was a mutualist when tested alone, all of the single strains we tested were commensals on hosts, benefiting from plant presence but not increasing host growth relative to uninoculated controls. However, 10-strain synthetic microbial communities increased both microbial productivity and duckweed growth more than the average single-strain inoculation and uninoculated controls, meaning that host-microbiome mutualisms can emerge from community interactions among microbes on hosts. The effects of community inoculation were sub-additive, suggesting at least some competition among microbes in the duckweed microbiome. We also investigated the relationship between L. minor fitness and that of its microbes, providing some of the first empirical estimates of broad fitness alignment between plants and members of their microbiomes; hosts grew faster with more productive microbes or microbiomes. IMPORTANCE There is currently substantial interest in engineering synthetic microbiomes for health or agricultural applications. One key question is how multi-strain microbial communities differ from single microbial strains in their productivity and effects on hosts. We tested 20 single bacterial strains and 2 distinct 10-strain synthetic communities on plant hosts and found that 10-strain communities led to faster host growth and greater microbial productivity than the average, but not the best, single strain. Furthermore, the microbial strains or communities that achieved the greatest cell densities were also the most beneficial to their hosts, showing that both specific single strains and multi-strain synthetic communities can engage in high-quality mutualisms with their hosts. Our results suggest that ~5% of single strains, as well as multi-strain synthetic communities comprised largely of commensal microbes, can benefit hosts and result in effective host-microbe mutualisms.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| 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 | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,002 |
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 tête enseignante, 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 ».