Author response: Ecology and evolution of viruses infecting uncultivated SUP05 bacteria as revealed by single-cell- and meta-genomics
Notice bibliographique
Résumé
Microorganisms help to drive a number of processes that recycle energy and nutrients, including elements such as carbon, nitrogen, and sulfur, around the Earth's ecosystems. Viruses that infect microbes can also affect these cycles by killing and breaking open microbial cells, or by reprogramming the cell's metabolism. However, as there are many different species of microbes and viruses —the vast majority of which cannot easily be grown in the laboratory— little is known about most virus–host interactions in natural ecosystems, especially in the oceans. In the world's oceans, the concentration of oxygen dissolved in the water changes in different regions and at different depths. ‘Oxygen minimum zones’ occur globally throughout the oceans at depths of 200–1000 meters, and climate change is causing these zones to expand and intensify. Although a lack of oxygen is sometimes considered detrimental to living organisms, oxygen minimum zones appear to be rich with microbial life that is adapted to thrive under oxygen-starved conditions. Sulfur-oxidizing bacteria are one of the most abundant groups of microbes in these oxygen minimum zones, and several of these bacteria are known to influence the recycling of chemical substances. Now, Roux et al. introduce a new method to identify viruses that infect the microbes in this environment, including those microbes that cannot be grown in the laboratory and which have previously remained largely unexplored. The genomes of 127 individual bacterial cells —collected from an oxygen minimum zone in western Canada— were examined. Roux et al. estimate that about a third of the sulfur-oxidizing bacterial cells are infected by at least one virus, but often multiple viruses infected the same bacterium. Five new genera (groups of one or more species) of viruses were also discovered and found to infect these bacteria. Looking for these new viral sequences in the DNA of this oxygen minimum zone's microbial community revealed that these newly discovered viruses persist in this region over several years. It also revealed that these viruses appear to only be found within the oxygen minimum zone. Roux et al. uncovered that these viruses carry genes that could manipulate how an infected bacterium processes sulfur-containing compounds; this is similar to previous observations showing that other viruses also influence cellular process (such as photosynthesis) in infected bacteria. As such, these newly discovered viruses might also influence the recycling of chemical elements within oxygen minimum zones. Together, Roux et al.'s findings provide an unprecedented look into a wild virus community using a method that can be generalized to uncover viruses in a data type that is quickly becoming more widespread: single cell genomes. This effort to understand virus–host interactions by looking in the genomes of individual cells now sets the stage for future efforts aimed to uncover the impact of viruses on bacteria in other environments across the globe.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,028 | 0,012 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».