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Enregistrement W7057267394

Investigation of the microbial diversity and characterization of new natural products produced by fungi and actinobacteria of Frobisher Bay

2017· article· en· W7057267394 sur OpenAlexaboutno aff

Notice bibliographique

RevueIslandScholar (University of Prince Edward Island) · 2017
Typearticle
Langueen
DomainePhysics and Astronomy
ThématiqueMagnetic confinement fusion research
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésActinobacteriaBayArcticExtreme environmentBiodiversityMicrobial ecologyMicroorganism
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Natural products (NPs) are an important source of pharmaceutical agents and are produced by a wide range of micro and macro organisms. Microorganisms, specifically bacteria within the order Actinomycetales and fungi, are prolific producers of NPs and are responsible for upwards of 70% of all clinically approved antibiotics. Due to the intensive investigation of these microorganisms, specifically from the terrestrial environment for NP discovery, the rate of reisolation of known compounds is high. One way to overcome this issue is to investigate unexplored and underexplored environments as a source of biodiverse microorganisms for natural product discovery.\nCanada’s Arctic remains a vast and largely undiscovered landscape due to its inaccessibility and harsh environment. Being so, the Arctic provides a unique niche, where members of the microbial community have evolved to “fit” this distinctive environment and must be capable of withstanding extreme cold, limited environmental resources and a range of other physical and biological factors. It is hypothesized Arctic microorganisms will have a unique secondary metabolome compared to their tropical counterparts based on environmental selection. Due to a lack of investigation of Canada’s Arctic for natural products, Frobisher Bay was selected as the study location for this investigation. The aims of this thesis were to characterize the bacterial and fungal community of Frobisher Bay and to discover new NPs from these microorganisms.\nIn order to assess the microbial community within Frobisher Bay, 454-pyrosequencing of the 16S rRNA gene and ITS region was used to determine the bacterial and fungal diversity respectively within sediment samples from Frobisher Bay. In order to achieve greater sequencing depth within the prolific NP producing Actinobacteria, Actinobacteria-specific 16S rRNA primers were used in addition to universal 16S rRNA primers. Overall, sites within Frobisher Bay were found to host high levels of taxonomically diverse microorganisms. The presence of large numbers of unknown phylotypes and the immense taxonomic diversity uncovered, make this region an intriguing area to explore from a NPs perspective.\nUsing a variety of isolation techniques, Actinobacteria and fungi were cultured from sediment samples collected from Frobisher Bay. In total, 90 Actinobacteria representing 25 distinct species, and 354 fungal isolates representing 54 species were cultured from this region. Of the fungal isolates, 9 appeared to be putatively novel based on sequencing of barcoding genes and morphological investigations. These isolates were particularly interesting from a NPs perspective, as they offered an untapped resource for NP discovery.\nIn order to prioritize isolates based on the production of new NPs, an LC-HRMS based screening method was used. This resulted in the isolation and characterization of several new NPs including a new hirsutellic acid analog obtained from Simplicillium aogashimaense RKAG 563, a new reduced perylene quinone compound obtained from Cadophora viticola RKAG 170 and two new cameronic acid analogs from Botrytis caroliniana RKAG 208. Investigation of the putatively novel fungal isolates was particularly fruitful for natural product discovery and resulted in the isolation of 17 new natural products. Investigation of Mortierella sp. RKAG 110 resulted in the characterization of mortiamides A-D, new cyclic heptapeptides containing five amino acids in the non-natural D-configuration. Examination of Sesquicillium spp. RKAG 571 and 186 led to the isolation of the new 11 residue peptaibols, tariuqins A-F containing the non-proteogenic amino acids (R)- and (S)-isovaline and aminoisobutyric acid, and to the isolation of the new cyclic decapeptides, auyuittuqamide A-D, containing three N-methylated amino acids. Lastly, exploration of putatively novel Tolypocladium species led to the isolation of several new tetramic acid containing compounds, iqalisetin A and B, and tolypoalbin.\nDue to the permanently cold environment from which they were isolated, the effect of fermentation temperature on NP product production in Actinobacteria from Frobisher Bay was investigated. As most standard lab fermentations occur at a non-ecologically relevant temperature of 30°C, fermentations at colder, more ecologically relevant temperatures (4°C and 15°C) was undertaken. Differences in NP production at each fermentation temperature were assessed using an LC-HRMS based chemical metabolomics method on a subset of cultured actinomycetes. Within the 15°C fermentations, the de novo induction of actinomycin was observed in Streptomyces sp. RKAG 337 and the upregulated production of two new compounds, landomycin AA and AB from Streptomyces sp. RKAG 290 was observed. Due to this upregulation, sufficient material was produced to enable structural characterization of these two compounds. The use of fermentation temperature to induce or increase the production of NPs is a useful tool to access previously inaccessible chemical diversity.\nOverall, Frobisher Bay is a rich resource for microorganisms as assessed by culture independent and dependent methods. The isolation of a large number of new NPs from microorganisms from this region, highlights the Arctic as a promising resource for NP discovery, reinforcing the notion that investigating unexplored environments for NP discovery is a very valuable tool in NPs research.

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)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,401
Score d'incertitude au seuil0,659

Scores Codex et Gemma par catégorie

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 ouverte0,0000,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,010
Tête enseignante GPT0,196
Écart entre enseignants0,186 · 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.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
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
Publié2017
Routes d'admission1
Résumé présentoui

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