MétaCan
Menu
Retour à la cohorte
Enregistrement W2141572369 · doi:10.1093/cid/civ548

Antifungals: From Genomics to Resistance and the Development of Novel Agents

2015· article· en· W2141572369 sur OpenAlexaff

Notice bibliographique

RevueClinical Infectious Diseases · 2015
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiquePlant Pathogens and Fungal Diseases
Établissements canadiensUniversity of Toronto
Organismes subventionnairesNational Institutes of HealthAstellas PharmaCidara Therapeutics
Mots-clésGenomicsResistance (ecology)Computational biologyBiologyGeneticsGeneGenome

Résumé

récupéré en direct d'OpenAlex

This book is a comprehensive and current assessment of antifungal drugs with a prominent emphasis on antifungal drug resistance and drug discovery. Invasive fungal infections result in approximately 1.4 million deaths annually, with most deaths due to infection with Cryptococcus, Candida, and Aspergillus species. Successful patient management requires antifungal therapy, yet treatment options are highly restricted, because existing systemic antifungal drugs comprise only limited chemical classes, including azoles, echinocandins, polyenes, and flucytosine. Patient outcomes are further compromised by the development of antifungal drug resistance. This book is organized by major themes and includes chapters on drug resistance and overcoming resistance, the discovery of novel microbe- and host-directed antifungal agents, and in vivo models of fungal infections. The effectiveness of each chapter reflects the prominent expertise of the authors. Chapters are well constructed and easy to read, with a comprehensive overview of critical issues related to each drug class or related topic, with attention to highly molecular facets of antifungal drug action and an eye toward either clinical experience or new applications. Collectively, the overall monograph works very well. The editors’ preface emphasizes that the book focuses on recent advances in deciphering the molecular mechanisms of drug resistance. The title, Antifungals, may suggest a broader view of antifungal drugs (eg, pharmacokinetic properties), but the subtitle, From Genomics to Resistance and the Development of Novel Agents, more aptly captures the essence of the book. The emphasis is apparent in the first 3 chapters, which provide overviews of classic membrane active antifungal drugs, azoles and polyenes, and the newer cell wall–active echinocandins, with detailed discussions of the molecular aspects of resistance in Candida and Aspergillus species. Antifungal resistance may result from selection for inherently resistant (primary resistant) species (eg, Candida krusei with azoles) or from acquired resistance during therapy. The molecular mechanisms for primary and acquired resistance are often the same and may reflect a different genetic wiring or prior selection from the environment, as in the case of Aspergillus resistant to highly active triazole agents. The chapter by Garcia-Effron is comprehensive and nicely incorporates into the dialogue computational models of the azole drug target, Cyp51a, illustrating changes in drug-target interactions following acquisition of resistance conferring mutations. The chapter by Katiyar and Edlind on echinocandin resistance provides a succinct overview of clinically related acquired resistance involving modification of glucan synthase subunits encoded by FKS genes. There is no discussion of adaptive compensatory mechanisms important for stabilizing cells in the presence of drug, but the authors do nicely describe the potential for other cellular mechanisms to modulate in vitro sensitivity. Biofilms are universal resistance mechanisms for fungi and bacteria, and Fox et al cover this subject effectively in their chapter. Overcoming and preventing resistance is a critical issue for all anti-infectives. To address this issue, Sanglard and Cowen revisit a combination strategy using existing drugs, as well as chemogenetics, to predict synergistic combinations of antifungal agents and other drugs, such as those mediated by stress modulator HSP90, to improve efficacy and help limit emergence of resistance. The past decade has seen major advances in dissection of molecular mechanisms of drug resistance. The power of this approach is very much on display in the chapter by Vandeputte, which describes the use of genomics, mutant analysis, and proteomics to identify novel resistance and/or drug tolerance mechanisms. There is an urgent need for new classes of antifungal agents, and Sebolai and Ogundeji explore the potential of Food and Drug Administration–approved drug libraries and natural products, including plant extracts affect microbial growth or host response. As a complement to this chapter, Hall and May describe well-defined biological processes, which may be used as potential antifungal targets, such as adenylyl cylase and carbonic anhydrase or other facets of cell wall glucan and/or mannan biosynthesis. Along with new antifungal drugs and chemical classes is the need to identify mode of action, which is nicely covered in the chapter by Znaidi, which describes classic and modern approaches to assessing mode of action. One of the important realizations of genetic studies on yeasts, such as Candida albicans and Candida glabrata, is how plastic these genomes behave, especially in response to drug stress. Genomic alternations in karyotype, especially aneuploidy, which result in gain or loss of partial segments of whole chromosomes, play an important role in up-regulating genetic mechanisms contributing to drug resistance and virulence. Loll-Krippleber et al very nicely describe the importance of genome integrity and the factors influencing it. Their chapter is somewhat out of place in the book and would have been better positioned at the end of the drug resistance mechanisms section, but this is a minor point. The development of agents that modulate host response to fungal pathogens is an important area that needs more attention. Courjol et al offer a helpful overview of the host response to fungal infections and risk factors for development of disease. Their chapter concisely describes the importance of macrophages, neutrophils, cytotoxic T-cell activation, and the inflammatory response in this process, as well as other critical adaptive and innate components of the immune response. It sets the stage for a chapter providing a provocative discussion of vaccine strategies and the potential value of exploiting CD8+ T-cell immunity for this purpose, as well as an overview of immunotherapy approaches. The concluding chapter by Coste and Amorim-Vaz provides a much-needed overview of the multitude of current animal models of infection used to study response to antifungal drugs and virulence factors including rodents, zebra fish, and moth larvae. This book will be extremely valuable to practitioners in medical mycology, including established and new researchers, clinicians and clinical microbiologists, and infectious disease specialists seeking a rapid update on the current state of antifungal drug resistance and antifungal development. Potential conflict of interest. D. S. P. receives grant support from the National Institutes of Health, Astellas, Scynexis, and Cidara. The author has submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.

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)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut 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 enseignants0,002
Score d'incertitude au seuil0,006

Scores du classifieur distillé par catégorie (deux têtes)

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

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.

Tête enseignante Opus0,059
Tête enseignante GPT0,331
Écart entre enseignants0,272 · 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'étudeSans objet
Domainenon disponible
GenreSynthèse

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

En bref

Citations12
Publié2015
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueClinical Infectious DiseasesMême sujetPlant Pathogens and Fungal DiseasesTravaux en français237 207