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Enregistrement W24326189 · doi:10.1016/j.aquatox.2013.11.004

Bioenergetics and dynamics of ciliary responses and systems biology of phototaxis in Chlamydomonas reinhardtii

2011· article· en· W24326189 sur OpenAlexfundno aff
Suphatra Adulrattananuwat

Notice bibliographique

Revuenon disponible
Typearticle
Langueen
DomaineNeuroscience
ThématiquePhotoreceptor and optogenetics research
Établissements canadiensnon disponible
Organismes subventionnairesTeck ResourcesInternational Zinc AssociationCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorCopper Development AssociationInternational Copper AssociationNickel Producers Environmental Research Association
Mots-clésPhototaxisChlamydomonas reinhardtiiBioenergeticsDynamics (music)BiologyPhysicsCell biologyBotanyGenetics

Résumé

récupéré en direct d'OpenAlex

The goal of this dissertation is to understand how a eukaryotic cell makes decisions. Chlamydomonas reinhardtii, a biciliated unicellular green alga, is used as our model organism. This organism has the ability to track the light using its photoreceptor called rhodopsin, which overlays the eyespot. The organism makes decisions to swim toward, away from, perpendicular to or to ignore the light using its slender arm-like structures called cilia. It can integrate several external inputs such as ion concentration and light intensity, and then process this information to adjust the steering of its cilia corresponding to its environment. We investigated how red light (670 nm) influences cell behavior. Most studies were done with a single cell held on a micropipette making it possible to observe the cilia behavior over a long time. The cell is illuminated with near-infrared light (peak at 870 nm) to avoid photoreceptor excitation. Ciliary movement is monitored using a quadrant photodiode detector (Chapter 2). Interpreted ciliary behavior parameters are the beating frequency (BF) and the stroke velocity (SV). Pulse stimuli were used to stimulate the mutant strain 806 (agg1), a negatively phototactic cell, whose beating frequency is in the same range as wild type. The "step-up" red light from the dark increases the beating frequency as an exponential function, y(t) = a*[1-exp(-t/b)] where y is a beating frequency, a is an amplitude and b is a time constant. On the other hand, the "step-down" red light drops the beating frequency transiently and recovers to its normal beating frequency of about 50 Hz in about 10 s. The 40 s duration pulse gave the maximum transient drop of the beating frequency. Using multi-sinusoidal red-light stimuli, I compared the behavior of the double mutant (cpc1-2) relative to the single mutant 806 (cpc1-2 was backcrossed to strain 806 so it is a single mutant with respect to 806). The mutant misses the part of the central-pair complex containing the enolase enzyme, one of the ciliary glycolytic enzymes that produces ATP in the cilia. Under a high constant-intensity of red light, the BF fluctuation is less than 2%. In the dark, BF of cpc1-2 is about 30 Hz which is lower than 806 probably due to less ATP being available. However, BF can be increased to the 806 level of 50 Hz by exposure to red light. A simple hypothesis is that red-light photosynthesis of the chloroplast makes ATP more available in the cell. In any case, sinusoidal red-light response of cpc1-2 shows that part of the early signal processing is approximately linear. In this case, cells respond to a decrease in light intensity by differentiating the red light signal. Our hypothesis is that the cell creates this signal to avoid futile usage of ATP. The transfer function describing this step is, G(s) = a*s*exp(-&tau*s) where &tau = 0.40 sec. In addition to this linear part, both strains have non-linear or approximately full-wave rectified signal processing of another red light created signal with a simple delay in time described by the transfer function, G(s) = a*exp(-&taustrain*s) where &tau806 = 1.18 sec and &taucpc1-2 = 0.37 sec. The longer delay time of 806 is likely due to the slow conversion of 3-phosphoglycerate (3PG) to adenosine triphosphate (ATP), in the glycolytic pathway, which is absent in the mutant. We hypothesize that the slow synthesis is due to the positive Gibbs free energy of two steps in the ciliary glycolytic pathway between 3PG and production of ATP and pyruvate. Furthermore, the beating frequency of red-light sinusoidal responses is stabilized by negative feedback. However, in the frequency range from 10 to 100 Hz in both strains that stabilizing negative feedback becomes positive and the BF jumps to a new state. In addition, I also studied how external ion concentration such as Ca2+, H+, and K+, and red light affect phototaxis of positively and negatively-phototactic cells (1117 and 806 respectively). I have tracked a cell population using the cell-tracking system for 10 s after stimulating them with green light (Chapter 4). Increasing [Ca2+]ext with a red light background enhances the motion of cells in the same and the opposite direction respectively according to cells' phototactic behavior under normal condition (pCa4 and pH 6.8). Increasing the pH tends to induce cells to move away from the light while increasing the [K+]ext gave the opposite results. Changing external ion concentration such as H+ and K+ affects the cell's membrane potential. Changing Ca2+ concentration affects both membrane potential and likely triggers internal signaling proteins such as IP3 and cAMP. Therefore, we hypothesize that cells may integrate these and potentially other signals to decide its phototaxis. Finally, I developed a technique that can be used to measure changes of the electric field across the plasma membrane of the cell in response to rhodopsin excitation. Rhodopsin excitation is thought to cause transmembrane ion influxes resulting in changes in the electric field across the plasma membrane. These electric field signals are then sensed in the cilia to enable phototactic steering of the cell (Chapter 5).

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,011
Score d'incertitude au seuil0,023

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,088
Tête enseignante GPT0,312
Écart entre enseignants0,224 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2011
Routes d'admission1
Résumé présentoui

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