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Physiological state of life in the buried biosphere: insights from amino acid racemization modeling and superresolution microscopy

2016· article· en· W4412328952 sur OpenAlexaboutno aff
Stefan Braun

Notice bibliographique

Revuenon disponible
Typearticle
Langueen
DomaineMedicine
ThématiqueWinter Sports Injuries and Performance
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésRacemizationBiosphereSuperresolutionResolution (logic)MicroscopyState (computer science)ChemistryBiologyComputer scienceArtificial intelligencePhysicsEcologyOpticsImage (mathematics)AlgorithmStereochemistry
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Ocean sediments harbor a microbial ecosystem that vertically extends into the seafloor for more than two kilometers in certain regions of the World Ocean. The activity of the microorganisms in this deep, buried biosphere bridges the biologi- cal and geological element cycles. At the seafloor, the number of cells per volume of sediment is generally very high (∼10^9 cells cm^−3 sediment). A steep decline in nutrient and energy availability with depth in the seabed, however, poses a strong constraint on the community size and metabolic rate of subsurface microorganisms. Consequently, cells in the deep seabed are less abundant (<10^2 to 10^8 cells cm^−3) and metabolize at the lowest rates reported for life on Earth. The persisting organ- isms in the deep seabed have to efficiently use the sparse amount of available energy to repair cell damage, maintain viability, and ultimately grow. Cell growth and metabolic activity in the deep biosphere are, however, poorly under- stood. It is unclear whether the majority of deeply buried microbes is (i) dormant, or (ii) spending available energy and nutrients for maintaining essential biomolecules and functions, or (iii) adapting to the low energy flux and thriving under balanced conditions over thousands to millions of years with an equilibrated number of cell divisions and cell deaths. The aim of this PhD project was to shed light on the physiological state of sub- seafloor microbial communities. The major goal was to determine the turnover of carbon in living microbial cells and in dead cells (utilization of cell detritus by ac- tive microbial populations) in the marine subsurface by sensitive analyses of stereo- isomeric amino acids and a mathematical model ("D:L-amino acid model"). Other important steps toward understanding the physiology and activity of sub- seafloor cells were the quantification of cell volumes and the cell-specific content of biomolecules (e.g. amino acids) by means of a cell separation and purification pro- cedure that enabled microscopic and chromatographic analyses of whole cells and subcellular compounds, respectively. Marine sediment cores were retrieved from a variety of regions including the Baltic Sea, the Labrador Sea, the North Atlantic and the Pacific Ocean. Samples were analyzed at world-leading institutions and research groups such as the Center for Geomicrobiology at Aarhus University (Denmark; host institution), the Max-Planck Institute for Marine Microbiology (Germany), the Kochi Institute for Core Sample Research (Japan), and the Organic Geochemistry Group at the University of Bremen (Germany). The systematic work on the separation of cells from the sediment matrix resulted in a new method that allowed for the first time the quantitative analyses of cellular biomolecules by high-performance liquid chromatography (HPLC) and fluorescence detection/mass spectrometry. The refined method involved density gradient centrifugation and fluorescence-activated cell sorting (FACS) for the purification of cells. Compared to a simple cell separation procedure without sorting, it provided superior purity of separated cells and more accurate estimates on the mean content of cellular biomolecules. The results demonstrated that sub-seafloor microbial cells have a cell-specific content of biomolecules that is up to four times lower than pre- vious estimates. For example, the cellular carbon content was 19-31 fg C cell^−1, which is at the lower end of previous estimations and will influence global estimates of microbial biomass and activity. Measurements of the body size of sub-seafloor microbial cells showed that the mean cell volumes decreased with sediment depth by up to one order of magnitude and were 10-100 times smaller than those of growing Escherichia coli cells. Furthermore, the cellular carbon density increased with sedi- ment depth from about 200 to 1000 fg C μm^−3, suggesting that cells decrease their water content and grow small cell sizes as adaptation to the low energy flux in the deep biosphere. Possibly, the low water content of the cells limits biomolecule decay and makes the cells less prone to intracellular damage from chemical reactions such as amino acid racemization, protein denaturation, or DNA depurination. Amino acid racemization modeling revealed that the low-biomass cells in the deep seabed divide on timescales of months to decades, feeding on the remains of dead cells. Thereby, the pool of detrital biomass (dead cells, i.e. microbial necromass) is turned over every few thousand years due to microbial recycling. Even though the cell generation times reported here are much higher than typical generation times obtained in laboratory cultures (hours to days) or other nutrient-rich environments, they are up to 100-fold faster than previous estimates and shift the maximal gener- ation times of ultra-slow microbial life from millennial toward decadal time scales. The obtained data will therefore influence our view of microbial activities on global element cycling over geologic time scales. Controlling factors of the microbial community size and its activity seemed to be (i) temperature and (ii) both the absolute and relative amount of microbial necromass. Our data indicated that cellular protein repair/replacement times and cell doubling times have to become faster to maintain enzymatic activity and cellular functions at higher temperatures, since amino acid racemization rates increase with increasing temperature. Furthermore, the results showed that the microbial community size is controlled by the concentrations of amino acids and possibly other high quality or- ganic compounds rather than by the concentrations of total organic matter, which apparently became more and more recalcitrant with age. Microbes preferentially utilized amino acids to conserve energy and synthesize biomass, highlighting the importance of microbial necromass as an important energy and carbon source, which was also reflected in a positive relationship between cell generation times and the amount of detrital amino acids theoretically available to each cell. With this study the author emphasizes the difference in the physiological state of cells from the (low-energy) environment and from (energy-rich) pure cultures and raises questions about the physiology and genetic potential of microbial life in the vast region that spans these two extremes. Given the large extent of marine sediment on Earth, this study on fundamental parameters of life in the deep seabed extends our knowledge of the energetic limits of life on our planet, is important for global estimates of microbial activity and biomass, and will help understanding the dynamics of microbial growth under extreme conditions in nature.

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 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)0,000
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: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,738
Score d'incertitude au seuil0,131

Scores Codex et Gemma par catégorie

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

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 Opus0,019
Tête enseignante GPT0,259
Écart entre enseignants0,240 · 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 tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

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
Publié2016
Routes d'admission1
Résumé présentoui

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