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Enregistrement W2169601236 · doi:10.1139/w05-003

A survey of the methods for the characterization of microbial consortia and communities

2005· review· en· W2169601236 sur OpenAlex

Pourquoi ce travail est dans la base

Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.

affAu moins un auteur déclare une institution canadienne dans l'instantané OpenAlex épinglé.
venuePublié dans une revue dont le pays d'attache est le Canada.

Notice bibliographique

RevueCanadian Journal of Microbiology · 2005
Typereview
Langueen
DomaineEnvironmental Science
ThématiqueMicrobial Community Ecology and Physiology
Établissements canadiensBiotechnology Research Institute
Organismes subventionnairesnon disponible
Mots-clésNucleic acidBiologyDNAComputational biologyPolymerase chain reactionPolymeraseIdentification (biology)Digital polymerase chain reactionGeneBiotechnologyBiochemical engineeringBiochemistry

Résumé

récupéré en direct d'OpenAlex

A survey of the available literature on methods most frequently used for the identification and characterization of microbial strains, communities, or consortia is presented. The advantages and disadvantages of the various methodologies were examined from several perspectives including technical, economic (time and cost), and regulatory. The methods fall into 3 broad categories: molecular biological, biochemical, and microbiological. Molecular biological methods comprise a broad range of techniques that are based on the analysis and differentiation of microbial DNA. This class of methods possesses several distinct advantages. Unlike most other commonly used methods, which require the production of secondary materials via the manipulation of microbial growth, molecular biological methods recover and test their source materials (DNA) directly from the microbial cells themselves, without the requirement for culturing. This eliminates both the time required for growth and the biases associated with cultured growth, which is unavoidably and artificially selective. The recovered nucleic acid can be cloned and sequenced directly or subpopulations can be specifically amplified using polymerase chain reaction (PCR), and subsequently cloned and sequenced. PCR technology, used extensively in forensic science, provides researchers with the unique ability to detect nucleic acids (DNA and RNA) in minute amounts, by amplifying a single target molecule by more than a million-fold. Molecular methods are highly sensitive and allow for a high degree of specificity, which, coupled with the ability to separate similar but distinct DNA molecules, means that a great deal of information can be gleaned from even very complex microbial communities. Biochemical methods are composed of a more varied set of methodologies. These techniques share a reliance on gas chromatography and mass spectrometry to separate and precisely identify a range of biomolecules, or else investigate biochemical properties of key cellular biomolecules. Like the molecular biological methods, some biochemical methods such as lipid analyses are also independent of cultured growth. However, many of these techniques are only capable of producing a profile that is characteristic of the microbial community as a whole, providing no information about individual members of the community. A subset of these methodologies are used to derive taxonomic information from a community sample; these rely on the identification of key subspecies of biomolecules that differ slightly but characteristically between species, genera, and higher biological groupings. However, when the consortium is already growing in chemically defined media (as is often the case with commercial products), the rapidity and relatively low costs of these procedures can mitigate concerns related to culturing biases. Microbiological methods are the most varied and the least useful for characterizing microbial consortia. These methods rely on traditional tools (cell counting, selective growth, and microscopic examination) to provide more general characteristics of the community as a whole, or else to narrow down and identify only a small subset of the members of that community. As with many of the biochemical methods, some of the microbiological methods can fairly rapidly and inexpensively create a community profile, which can be used to compare 2 or more entire consortia. However, for taxonomic identification of individual members, microbiological methods are useful only to screen for the presence of a few key predetermined species, whose preferred growth conditions and morphological characteristics are well defined and reproducible.

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.

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)0,002
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: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,989
Score d'incertitude au seuil0,997

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,002
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,001
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 Opus0,071
Tête enseignante GPT0,328
Écart entre enseignants0,257 · 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