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Enregistrement W4403584751 · doi:10.3389/fgene.2024.1485895

Editorial: Microbial OMICS, an asset to accelerate sustainability in agricultural and environmental microbiology

2024· editorial· en· W4403584751 sur OpenAlexaff
Adolphe Zézé, Mohamed Hijri

Notice bibliographique

RevueFrontiers in Genetics · 2024
Typeeditorial
Langueen
DomaineEnvironmental Science
ThématiqueMicrobial Community Ecology and Physiology
Établissements canadiensUniversité de Montréal
Organismes subventionnairesnon disponible
Mots-clésAgricultureSustainabilityOmicsAsset (computer security)MetagenomicsMicrobial ecologyBiotechnologyEnvironmental biotechnologyBiologyBusinessComputer scienceEcologyBioinformaticsBacteriaGenetics

Résumé

récupéré en direct d'OpenAlex

Microorganisms provide numerous ecosystem services to humans, allowing natural systems to benefit from a genetic reservoir essential for their fundamental functioning and sustainability (Rodrigues-Filho et al. 2023). They also play pivotal roles in the functioning of global ecosystems (Li et al. 2023;Liu et al. 2019). The advancement of microbial OMICS has enabled accurate elucidation of microbial functions across diverse ecosystems (Kaur et al. 2023), resulting in the identification and characterization of numerous provisioning services, biological processes, and supporting services (Beale et al. 2022). Moreover, microbial OMICS research has contributed to the advancement of applied biotechnologies and innovations in domains such as food security, agriculture, aquaculture, human health, animal health, and environmental protection (Su et al. 2024;Natnan et al. 2021;Chen et al. 2023;Goossens et al. 2022). The knowledge generated by microbial OMICS technologies, along with the development of related applied biotechnology, represents significant progress in sustainable agriculture and environmental management (Hijri 2023).The use of OMICS technologies enables the monitoring of soil health and productivity within agroecosystems. It has been reported that the utilization of specific microbes within agroecosystems, along with the type of soil management, can influence soil microbial community structure and function, consequently impacting soil health and crop productivity (Bertola et al. 2021). In a review, Adedayo and Babalola (2023) highlighted the significance of plant genomics in promoting the bioeconomy and the potential offered by advances in plant breeding techniques. Along with persisting challenges of underdevelopment and shifts in average weather conditions, the issue of food scarcity remains unresolved. Consequently, advances in crop production offer potential solutions to tackle these challenges. Furthermore, their review discussed the benefits of beneficial microbes in promoting crop growth and outlined the use of OMICS techniques to characterize plant-microbe interactions (Figure 1). Using 16S rRNA gene metabarcoding targeting bacterial communities, Duan et al. (2023b) demonstrated that the cultivation of Morchella esculenta in fallow paddy fields and drylands can alter the diversity of soil bacteria, affecting soil health and rice productivity. Their findings suggested that M. esculenta cultivation may enhance bioavailability of soil phosphorus and potassium in paddy fields, and potassium in dryland soil. M. esculenta cultivation had a modest impact on alpha diversity, and it influenced the abundance of certain genera of soil bacteria. Their functional annotation analysis indicated that M. esculenta cultivation might reduce methane production potential in paddy field soil and enhance nitrogen cycling in dryland soil. They performed a network analysis and correlation analysis, which revealed that Gemmatimonas, Bryobacter, and Anaeromyxobacter were key bacterial genera regulating soil chemical properties in paddy field soil under M. esculenta cultivation, while Bryobacter, Bacillus, Streptomyces, and Paenarthrobacter were key taxa associated with potassium accumulation in dryland soil. Arunrat et al. (2023) compared the variability of soil bacterial communities in maize monoculture and the fallow phase of rotational shifting cultivation fields in Northern Thailand. They selected a continuous 5-year fallow field (CF-5Y) and a continuous 5-year maize cultivation field (M-5Y) with similar microclimate, topography, and duration of field activities. Soil samples were collected from the surface layer at both sites every 3 months for one year. Analysis of soil bacterial diversity and composition was conducted using 16S rRNA gene amplicon sequencing. They observed that CF-5Y soil maintained greater stability in bacterial richness and diversity across seasons than M-5Y soil. Notably, fertilization and tillage practices in M-5Y were found to enhance both the diversity and richness of soil bacteria. The study concluded that changes in soil bacterial diversity may result from multifactorial conditions such as land management practices, soil physicochemical properties, weather conditions, and vegetation cover (Arunrat et al. 2023).Another finding relates to how soil health and crop productivity can be impacted by organic amendment into plant-fungus intercropping systems. Duan et al. (2023a) assessed the impact of bagasse amendment in a sugarcane -Dictyophora indusiata intercropping system on soil health through a field experiment comprising three treatments: bagasse amendment alone, (2) sugarcane amended with bagasse, and the control. Soil chemistry, soil bacterial and fungal diversity using amplicon sequencing, and metabolite composition were analyzed to elucidate the mechanisms underlying the effects of this intercropping system on soil properties. Soil chemistry analyses revealed higher levels of several soil nutrients such as nitrogen and phosphorus in the bagasse application compared to the control. Bacterial diversity was greater in the bagasse application than other treatments, while fungal diversity was lower in the bagasse-amended sugarcane than in other treatments. Soil metabolome analysis revealed significantly lower abundance of carbohydrate metabolites in the bagasse application compared to the control and the bagasse-amended sugarcane. They suggested that the sugarcane amended with bagasse can improve soil health in this intercropping system.Two studies on microbial genome sequencing revealed new species. A Bradyrhizobium . isolated from polluted sediments of a lake in China was identified as a new free-living species Bradyrhizobium roseus (Zhang et al. 2023). B. roseus displays considerable heterogeneity, exhibiting several functional distinctions from previously described Bradyrhizobium genomes. Another study reported a new endophytic fungus, Cladosporium angulosum, harboring N uptake-related genes with the potential to enhance plant growth (Yang et al. 2023). Amon et al. (2023) utilized 16S rRNA gene analyses to explore bacterial biogeography and ecosystem services in soils of Côte d'Ivoire. Within bacterial communities comprising 48 phyla, 92 classes, 152 orders, 356 families, and 1,234 genera in Côte d'Ivoire soils, a core bacteriobiome was identified. The distribution of the core genera, along with the 10 major phyla, was influenced by environmental factors including latitude, and soil pH, Al, and K. The predominant distribution pattern observed for the core bacteriobiome was vegetation-independent. Concerning predicted functions, all core bacterial taxa were implicated in assimilatory sulfate reduction, while atmospheric dinitrogen (N2) reduction was exclusively associated with the genus Bradyrhizobium. Carroll et al. (2023) employed phylogenomic and comparative genomics to characterize the population structure and functional potential of 110 Micrococcus strains, comprising 104 publicly available genomes and six individuals isolated from South Africa. In terms of functional potential, genes for antimicrobial compounds, including macrolides, beta-lactams, and aminoglycosides (in 81, 61, and 44 of 110 genomes, respectively), were identified across Micrococcus genomes. Genome-wide analyses enabled Ma et al. (2023) to understand variation in Mycoplasma gallisepticum, one of the primary causative agents of chronic respiratory diseases in poultry. It was revealed that the intensity of M. gallisepticum biofilm formation strongly correlates with chronic infection, and strains with stronger biofilm-forming abilities exhibit reduced sensitivity to 17 tested antibiotics. Putative key genes associated with biofilm formation, identified through genome-wide analysis of two strains with contrasting biofilm formation, included ManB, oppA, oppD, PDH, eno, RelA, msbA, deoA, gapA, rpoS, Adhesin P1 precursor, S-adenosine methionine synthetase, and methionyl tRNA synthetase.Two investigations underscored the significance of microbial OMICS in elucidating natural environmental microbiological processes. de Oliveira et al. ( 2024) utilized shotgun metagenomic sequencing data from water column samples to investigate the resistome and bacterial diversity of two small lakes in the Southern Pantanal region of Brazil. The Abobral lake displayed the highest diversity and abundance of antibiotic resistance genes, antibiotic resistance classes, phyla, and genera. RPOB2 was identified as the most abundant antibiotic resistance gene, and its associated resistance class was the most abundant class. Pseudomonadota emerged as the dominant phylum across all sites, with Streptomyces being the most prevalent genus. Ye et al. (2023) isolated a thermophilic Bacillus subtilis strain from nicotine waste that was resistant to nicotine and possessed high capability to degrade tobacco-derived organics. Whole-genome sequencing revealed that this B. subtilis strain also exhibited antibacterial properties, enabling its use in organic fertilizers capable of biological control.

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)0,004
score de la tête « metaresearch » (Gemma)0,013
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: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,038
Score d'incertitude au seuil0,125

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,013
Méta-épidémiologie (sens strict)0,0030,001
Méta-épidémiologie (sens large)0,0030,002
Bibliométrie0,0040,002
Études des sciences et des technologies0,0020,002
Communication savante0,0070,005
Science ouverte0,0030,001
Intégrité de la recherche0,0090,008
Charge utile insuffisante (le modèle a refusé de juger)0,0380,024

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 Opus0,004
Tête enseignante GPT0,221
Écart entre enseignants0,218 · 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
GenreÉditorial

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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