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Enregistrement W7113571119

Mouse Tracheal Epithelial Cells (mTECs) as a Tool to Study the Role of BPIFA1 in Influenza A Infection

2024· other· en· W7113571119 sur OpenAlexaff

Notice bibliographique

RevueWhite Rose eTheses Online (University of Leeds, The University of Sheffield, University of York) · 2024
Typeother
Langueen
Domaine
Thématique
Établissements canadiensInstitute of Infection and Immunity
Organismes subventionnairesnon disponible
Mots-clésRespiratory tractRespiratory epitheliumEpitheliumVirusInnate immune systemCellPathogenGene
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Abstract The respiratory epithelium is a major physical barrier to infections and provides a robust innate defensive shield through the concerted actions of the mucociliary epithelial layer and its secreted chemical components. Influenza A virus (IAV) is a major human pathogen that overcomes these defences to cause disease. The mechanism that the virus uses to infect the airway remains to be fully elucidated. We have employed primary airway cells grown in 3D cultures as models to understanding the role of epithelial cells in homeostasis and infectious disease. In these cells differentiation occurs when the confluent cell layer develops on the semi-permeable insert with the cells fed with media underneath, termed an air liquid interface (ALI) condition. Studies using mice tracheal epithelial cells (mTECs) at the ALI have recently shown that BPIFA1 (Bacterial Permeability increasing fold containing Family A member 1), a respiratory tract secreted protein, protects the airway from IAV infection. The mechanism for this remains unknown and it was assumed that the infection was occurring through ciliated cells. In this thesis I have established and validated mTECs grown at an ALI as a tool for infection studies. I conducted a genome-wide transcriptional analysis to investigate global alterations in gene expression as the cells transitioned from isolated cells, through a basal cell intermediate phenotype, to full mucociliary differentiation. The cultures represent a model of the native tracheal epithelium. This analysis identified multiple genes as being up regulated during this process and serves as a resource for target gene identification. Using published single cell RNAseq data we could show that Bpifa1 expression is seen in several cell types with by far the highest expression being seen in the secretory cells. A comparative expression analysis showed that Bpifa1 was the most highly expressed member of the larger Bpif gene family in mTECs and confirmed that the closest murine paralog of the gene, Bpifa5, was not expressed in these cells, and would not be likely to serve a similar function. Using IF microscopy I confirmed that IAV did not infect BPIFA1 positive cells in mTEC cultures and was not commonly associated with ciliated cells at the early stages of infection. To address issues of cell specificity, I infected undifferentiated mTECs (lacking the mature epithelial phenotype) and could show that these were infected, despite the absence of ciliated cells. Levels of infection 2 | Page were less than was seen in differentiated mTECs. A genome wide transcriptional study showed cells of both phenotypes (basal cell intermediate, and full mucociliary differentiation phenotypes) upregulated multiple interferons stimulated genes (ISGs), albeit with lower response in the undifferentiated cells. I identified the gut antimicrobial protein gene Lypd8, as a potential novel ISG. I employed this infection model to establish an assay for IAV infection of undifferentiated mTECs, which can be utilized to examine the role of BPIFA1 in IAV anti-viral responses. To investigate this further, I generated several recombinant BPIFA1 protein expression constructs that exhibit sequence differences in a presumptive functional domain at the N-terminus of the protein for use in this infection assay. Comparative analysis showed that this repeat region is highly variable between species and is longer in rodents. I also generated a series of short peptides corresponding to the repeat region in this domain. Both sets of BPIFA1 derived reagents could be investigated for their ability to modulate IAV infection and to define more fully the functional mechanism that BPIFA1 employs against IAV infection. My results show that mTECs are a good model for studies investigating IAV infections. Undifferentiated mTECs can be used in a simple quantitative infection assay to unravel the contributions of specific regions of BPIFA1 in regulating IAV infection.

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 distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: Qualitatif
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,279
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0020,002
Études des sciences et des technologies0,0000,002
Communication savante0,0000,000
Science ouverte0,0030,002
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 Opus0,017
Tête enseignante GPT0,234
Écart entre enseignants0,217 · 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 tête enseignante, pas un consensus.

Devis d'étudeQualitatif
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

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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