An experimentally evolved variant of RsmA confirms its central role in the control of <i>Pseudomonas aeruginosa</i> social motility
Notice bibliographique
Résumé
Abstract Bacteria can colonize a variety of different environments by modulating their gene regulation using two-component systems. The versatile opportunistic pathogen Pseudomonas aeruginosa has been studied for its capacity to adapt to a broad range of environmental conditions. The Gac/Rsm pathway is composed of the sensor kinase GacS, that detects environmental cues, and the response regulator GacA, that modulates the expression of a specific genes. This system, through the sRNA repressors RsmY and RsmZ, negatively controls the activity of the protein RsmA, which is centrally involved in the transition from chronic to acute infections by post-transcriptionally regulating several virulence functions. RsmA positively regulates swarming motility, a social surface behaviour. Through a poorly defined mechanism, RsmA is also indirectly regulated by HptB, and a Δ hptB mutant exhibits a severe swarming defect. Since a Δ hptB mutant retains all the known functions required for that type of motility, we used an experimental evolution approach to identify elements responsible for its swarming defect. After a few passages under swarming conditions, the defect of the Δ hptB mutant was rescued by the emergence of spontaneous single nucleotide substitutions in the gacA and rsmA genes. Since GacA indirectly represses RsmA activity, it was coherent that an inactivating mutation in gacA would compensate the Δ hptB swarming defect. However, the effect of the mutation in rsmA was unexpected since RsmA promotes swarming; indeed, using expression reporters, we found that the mutation that does not abolish its activity. Instead, using electrophoretic mobility shift assays and molecular simulations, we show that this variant of RsmA is actually less amenable to titration by its cognate repressor RsmY, supporting the other phenotypes observed for this mutant. These results confirm the central role of RsmA as a regulator of swarming motility in P. aeruginosa and identify residues crucial for RsmA function in social motility. Author summary Bacteria need to readily adapt to their environment. Two-component systems (TCS) allow such adaption by triggering bacterial regulation changes through the detection of environmental cues. The opportunistic pathogen Pseudomonas aeruginosa possesses more than 60 TCS in its genome. The Gac/Rsm is a TCS extensively studied for its implication in virulence regulation. This system regulates the transition between chronic and acute bacterial infection behaviours. To acquire a better understanding of this regulation, we performed a directed experimental evolution on a swarming-deficient mutant in a poorly understood regulatory component of the Gac/Rsm pathway. We observed single nucleotide substitutions that allowed restoration of a swarming phenotype similar to the wild-type behaviour. More specifically, mutations were found in the gacA and rsmA genes. Interestingly, the observed mutation in rsmA does not result in loss of function of the protein but rather alters its susceptibility to repression by its cognate interfering sRNA. Since modification in the RNA sequence of RsmA results in the rescue of swarming motility, we confirm the central role of this posttranscriptional repressor in this social lifestyle.
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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 | 0,000 | 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) | 0,002 | 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 ».