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Enregistrement W4389626867 · doi:10.3389/fmicb.2023.1346581

Editorial: Ecology and molecular biology of bloom-forming cyanobacteria

2023· editorial· en· W4389626867 sur OpenAlexaff
George S. Bullerjahn, R. Michael L. McKay, P. Visser

Notice bibliographique

RevueFrontiers in Microbiology · 2023
Typeeditorial
Langueen
DomaineEnvironmental Science
ThématiqueAquatic Ecosystems and Phytoplankton Dynamics
Établissements canadiensUniversity of Windsor
Organismes subventionnairesnon disponible
Mots-clésCyanobacteriaEcologyBloomBiologyMolecular ecologyEvolutionary biologyBacteriaGeneticsSociology

Résumé

récupéré en direct d'OpenAlex

Given the worldwide expansion of cyanobacterial harmful algal blooms (cHABs), this Research Topic seeks to highlight the threats that bloom events pose to environmental and human health. As many studies link severity of cHABs to a warming climate and changing precipitation patterns, such events are expected to grow, with cHABs increasing in distribution, duration and frequency, contributing to unbalanced and degraded ecosystems. Addressing this global concern, research is aimed at understanding the environmental factors contributing to bloom formation and decline, toxin and metabolite synthesis, bloom ecology, and cHAB mitigation. This Research Topics collection of papers, largely drawn from contributions to the 12 th International Conference on Toxic Cyanobacteria, aims to showcase the state of the science related to cHABs, which may point to potential solutions to this growing threat to our freshwater resources.Several papers contributed to the Research Topic addressed community structure and the ecology of blooms. Whereas colonial Microcystis has become synonymous with blooms, there is increased recognition of community diversity between bloom locations and even within a bloom itself. In part, this is attributed to more widespread adoption of metabarcoding and genomics approaches as evidenced by each of the studies highlighted here. Beyond methodological advances, community structure often reflects environmental gradients to which communities are exposed. One such gradient is the fluvial-lacustrine continuum. Surveying bloom-forming regions of the Laurentian Great Lakes, Crevecoeur et al. identified a clear shift in dominance of the cyanobacterial communities between river and lake, yet also noted strong connectivity and dispersal of taxa within the system as a whole. Elsewhere, seasonality can play a role in shaping community structure. In Florida's Lake Okeechobee, Lefler et al. showed that cyanobacterial communities within the lake are significantly different between the wet and dry seasons. Also noted from this study was that the dominant cyanobacterial bloom formers in this lake maintain distinct bacterial associations that may confer competitive advantages across spatial and temporal scales.In many cases, underlying environmental gradients are nutrients, the parameter conventionally recognized as dominant in the 'bottom-up' control of cHABs. The important role of nutrients in shaping community structure was assessed in several of the contributing articles. Chen et al. frame the role of nutrients in a management framework, noting that closed-lake management practices adopted to control nutrient loading in the Taihu Basin River Network were successful at mitigating blooms of Microcystis. Using a metagenomic approach to compare the taxonomic and functional structure of the bacterioplankton community between open and closed lakes, differences were detected at fine taxonomic resolution (genus and species), but not extending to functional genes maintained by keystone taxa. In another managed system, Feng et al. assessed seasonal variability of microbial community composition in a subtropical reservoir following completion of a multi-year ecological restoration project aimed to reduce nutrient loading from adjacent tributaries. Their study showed negligible variability in community structure related to seasonality; however, the surveys showed enrichment of cyanobacterial communities in benthic samples pointing to possible internal loading as a nutrient source. Finally, Kim et al. examined microbial community structure and the presence of cyanotoxins in aerosols generated from wind-driven wave action in South Korea's Nakdong River. There is increased recognition of the potential threat of aerosols as a vector for cyanotoxin exposure, a concern reinforced by this study that showed toxigenic Microcystis to be one of the dominant genera in the aerosol microbiome.Three articles in this Research Topic investigated diverse aspects of natural control of cyanobacterial blooms, ranging from the role of cyanophages and chytrids on cyanobacteria and the viral influence on phytoplankton community dynamics. McKindles et al. focused on understanding the diversity and role of cyanophages in bloom control in Sandusky Bay, revealing the molecular characterization of Planktothrix specific cyanophages. Transcriptomic analysis revealed only low levels of viral gene expression despite the highly abundant cyanophages over the course of multiple years. The study also aimed to design monitoring methods for bloom lysis events, where potentially toxins are being released. Wagner et al. explored the dynamics of chytrid (Rhizophydium sp.) infections in Planktothrix agardhii blooms, with modified environmental conditions in mesocosms to explore infection prevalence. The results identified temperature and water flow as crucial factors in chytrid prevalence. The study provides valuable insights into control measures to reduce blooms. Lastly, Peng et al. investigated viral influences on phytoplankton community succession in the Three Gorges Reservoir, emphasizing the multiple roles viruses play in summer bloom dynamics. The viral lysis of eukaryotes and increase of nutrients due to the lysis of bacterioplankton appeared to be beneficial for the success of cyanobacteria. Together, these studies provide comprehensive insights into the complex interactions shaping cyanobacterial blooms, offering valuable knowledge for developing effective control strategies and safeguarding water ecosystems.Concluding the collection, three papers present data on metabolites that include both the synthesis of the common cyanotoxin, microcystin, as well as other products that arise in concert with bloom events. Extending prior work on the temperature dependence of microcystin accumulation in Microcystis sp. at lower temperatures, Roy et al. showed that a wild type Microcystis toxin-producing strain, has a growth advantage over its DmcyB (nontoxic) mutant strain at both low (20 o C) and high temperature (30 o C and 35 o C), and that cellular quotas of soluble microcystins are lower at higher temperature. However, higher temperature yields a shift in the intracellular toxin pool. This paper helps provide a better understanding of the role of microcystins in adaptation of Microcystis sp. to long-term and diel temperature shifts.The papers by Zhou et al. and Lee et al. examined other metabolites and factors associated with blooms that may also affect environmental and human health. Zhou and colleagues have studied exudates of Microcystis aeruginosa that can be inhibitory to aquatic life, and in this paper, they employed LC/MS to characterize exudates from nontoxic and toxic Microcystis strains during exponential and stationary phases of growth. Whereas the toxinproducing strain produced a higher diversity of exudate compounds, the nontoxic strain produced higher concentrations of potentially ecotoxic metabolites. This work demonstrated that even nontoxic bloom formers can produce compounds that degrade ecosystem health. The paper by Lee and colleagues raises awareness of both disinfection byproducts by water treatment of cHABs, and of potential pathogens (Legionella sp.) and antibiotic resistance genes associated by blooms. Evidently, bloom biomass may afford multiple threats to health which extend past the well-known consequences of microcystin exposure.

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)0,005
score de la tête « metaresearch » (Gemma)0,018
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 enseignants0,019
Score d'incertitude au seuil0,063

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0050,018
Méta-épidémiologie (sens strict)0,0050,002
Méta-épidémiologie (sens large)0,0050,005
Bibliométrie0,0050,002
Études des sciences et des technologies0,0030,003
Communication savante0,0080,006
Science ouverte0,0050,002
Intégrité de la recherche0,0140,015
Charge utile insuffisante (le modèle a refusé de juger)0,0190,015

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 Opus0,003
Tête enseignante GPT0,216
Écart entre enseignants0,213 · 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

Citations3
Publié2023
Routes d'admission1
Résumé présentoui

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