Microorganisms in sea ice melt pools as a source of ultra-violet radiation absorbing metabolites
Notice bibliographique
Résumé
Natural products have many uses in today’s society, from disease therapeutics to\ncosmetic applications. One such application of natural products is use as an active\ningredient in commercial sunscreens. Ultra-violet (UV) radiation exposure can result in\na range of harmful side effects from a minor burn to the induction of melanoma. Due to\nthe hazards associated with UV exposure, there is a need for safe and effective natural\nsunscreens. Microbes are known to produce structurally diverse natural products with\ngreatly varied functions. One potential role of microbial natural products is to act as UV\nprotectants for the producing organism. For this thesis we wanted to describe the\ncultivable microbial community of sea ice melt pools to determine if microbes in this\nhabitat are resistant to UVB radiation, and if their mechanism of resistance was via the\nproduction of UV protectants. Thus, microbes living in high UV intense habitats are of\ninterest for this thesis. One such habitat is sea ice melt pools in Canada’s Arctic. During\nthe early summer months the sea ice begins to melt forming melt pools. Due to the\nconstant sun exposure, coupled with the reflective property of the ice, microbes present\nin these pools endure extreme levels of UV radiation. Microorganisms have three\nmechanisms in which they can survive exposure to UV radiation. They can produce\nspores, have DNA repair mechanisms, or they can produce UV-absorbing metabolites.\nWith this knowledge it was hypothesized that microbes living in these melt pools would\nbe resistant to UV radiation via the production of UV-absorbing metabolites. Water\nsamples were collected from sea ice melt pools in Nunavut and the cultivable microbial\ncommunity was identified via sequencing of the 16S rRNA gene (bacteria) and the\nITS/28S rRNA genes (fungi). Phylogenetic analysis revealed that the microbes belonged to 26 different species. Of these 26 species two of the organisms, Frigidiomyces\naurantiacum and Polaromyces triangulaformis, were discovered in this study and were\ndescribed during the course of the research. Each of the 26 organism’s temperature\ngrowth range, nutrient requirements, ability to survive a freeze thaw cycle, and\nresistance to UVB radiation were determined. Post exposure to UVB radiation,\ncompounds produced by each organism was extracted to determine if UV-absorbing\nmetabolites were being produced. The crude extracts were then analyzed using HPLCHRMS.\nOf the 26 organisms, seven were true psychrophiles, 17 could survive with\nminimal nutrients, all of the organisms tested remained viable after a single freeze-thaw\ncycle, and 20 were resistant to exposure to UVB radiation. HPLC-HRMS analysis of\nthe crude extracts revealed that four strains produced mycosporines or mycosporine-like\namino acids. One bacterium, Rhodococcus sp. RKAT245, produced a single\nmycosporine-like amino acid, shinorine. From the fungal library, Bulleromyces albus\nproduced mycosporine-glutaminol, Dioszegia sp. RKAT 238 produced mycosporineglutaminol,\nmycosporine-glutaminol-glucoside, and mycosporine-glutamicol-glucoside,\nwhile Frigidiomyces aurantiacum produced mycosporine-glutaminol-glucoside.
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 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 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
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 ».